2011
Lenci, Alessandro
Composing and Updating Verb Argument Expectations: A Distributional Semantic Model Conference
Proceedings of the 2nd Workshop on Cognitive Modeling and Computational Linguistics, 2011, ISBN: 9781932432954.
@conference{ 11568_148440,
title = {Composing and Updating Verb Argument Expectations: A Distributional Semantic Model},
author = {Alessandro Lenci},
url = {http://aclweb.org/anthology/W/W11/W11-0607.pdf},
isbn = {9781932432954},
year = {2011},
date = {2011-01-01},
booktitle = {Proceedings of the 2nd Workshop on Cognitive Modeling and Computational Linguistics},
pages = {58–66},
abstract = {The aim of this paper is to present a computational model of the dynamic composition and update of verb argument expectations using Distributional Memory, a state-of-the-art framework for distributional semantics. The experimental results conducted on psycholinguistic data sets show that the model is able to successfully predict the changes on the patient argument thematic fit produced by different types of verb agents.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
The aim of this paper is to present a computational model of the dynamic composition and update of verb argument expectations using Distributional Memory, a state-of-the-art framework for distributional semantics. The experimental results conducted on psycholinguistic data sets show that the model is able to successfully predict the changes on the patient argument thematic fit produced by different types of verb agents.
2010
Lenci, Alessandro
The Life Cycle of Knowledge Book Chapter
In: Ontologies and the Lexicon. A Natural Language Processing Perspective, pp. 241–257, Cambridge University Press, CAMBRIDGE, 2010, ISBN: 9780521886598.
@inbook{ 11568_135921,
title = {The Life Cycle of Knowledge},
author = {Alessandro Lenci},
isbn = {9780521886598},
year = {2010},
date = {2010-01-01},
booktitle = {Ontologies and the Lexicon. A Natural Language Processing Perspective},
pages = {241–257},
publisher = {Cambridge University Press},
address = {CAMBRIDGE},
abstract = {This book deals with ontological and lexical knowledge resources. The ontolex interface (See chapter 10 this volume) is an attempt to answer to the increasing need of modeling the complex interrelationship between lexicons and ontologies, which are more and more assuming the form of rich ontolexical resources. I will use this term to stress the importance of investigating the substantial areas of overlapping between ontologies and lexicons, as a step toward a better understanding of their individual characters. In this chapter, I will focus on the interaction between ontolexical knowledge systems and a specific context of use that shapes their dynamics, i.e. natural language processing (NLP). Therefore, methods, tools and applications for NLP are here analyzed under the perspective of how they affect the life cycle of knowledge.},
keywords = {},
pubstate = {published},
tppubtype = {inbook}
}
This book deals with ontological and lexical knowledge resources. The ontolex interface (See chapter 10 this volume) is an attempt to answer to the increasing need of modeling the complex interrelationship between lexicons and ontologies, which are more and more assuming the form of rich ontolexical resources. I will use this term to stress the importance of investigating the substantial areas of overlapping between ontologies and lexicons, as a step toward a better understanding of their individual characters. In this chapter, I will focus on the interaction between ontolexical knowledge systems and a specific context of use that shapes their dynamics, i.e. natural language processing (NLP). Therefore, methods, tools and applications for NLP are here analyzed under the perspective of how they affect the life cycle of knowledge.
Marotta, Giovanna; Lenci, Alessandro; Meini, L.; Rovai, F.
Space in Language. Proceedings of the Pisa International Conference Miscellaneous
2010, ISBN: 9788846729026.
@misc{ 11568_139670,
title = {Space in Language. Proceedings of the Pisa International Conference},
author = {Giovanna Marotta and Alessandro Lenci and L. Meini and F. Rovai},
isbn = {9788846729026},
year = {2010},
date = {2010-01-01},
publisher = {ETS},
address = {PISA},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
Marotta, Giovanna; Lenci, Alessandro; Meini, L; Rovai, Francesco
Space in Language Book
ETS, PISA, 2010.
@book{<LineBreak> 11568_140935,
title = {Space in Language},
author = {Giovanna Marotta and Alessandro Lenci and L Meini and Francesco Rovai},
year = {2010},
date = {2010-01-01},
urldate = {2010-01-01},
pages = {1–610},
publisher = {ETS},
address = {PISA},
keywords = {},
pubstate = {published},
tppubtype = {book}
}
Zarcone, A.; Lenci, Alessandro
Priming effects on event types classication: Effects of word and picture stimuli Conference
Proceedings of CogSci 2010, Cognitive Science Society, 2010, ISBN: 9780976831860.
@conference{ 11568_138425,
title = {Priming effects on event types classication: Effects of word and picture stimuli},
author = {A. Zarcone and Alessandro Lenci},
url = {http://mindmodeling.org/cogsci2010/papers/0464/paper0464.pdf},
isbn = {9780976831860},
year = {2010},
date = {2010-01-01},
booktitle = {Proceedings of CogSci 2010},
pages = {1886–1891},
publisher = {Cognitive Science Society},
abstract = {Event types (ET) have been widely addressed in linguistic literature, but few studies have dealt with the questions of how they are represented, retrieved and processed in the mental lexicon. We report two experiments in which ET categories were found to give rise to semantic priming effects, both with word and picture stimuli. These effects are argued to provide empirical correlates for ET categories in the mental lexicon not only at the lexical level but also at a deeper conceptual level.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Event types (ET) have been widely addressed in linguistic literature, but few studies have dealt with the questions of how they are represented, retrieved and processed in the mental lexicon. We report two experiments in which ET categories were found to give rise to semantic priming effects, both with word and picture stimuli. These effects are argued to provide empirical correlates for ET categories in the mental lexicon not only at the lexical level but also at a deeper conceptual level.
Huang, C. R.; Calzolari, N.; Gangemi, A.; Lenci, Alessandro; Oltramari, A.; Prevot, L.
Ontologies and the Lexicon. A Natural Language Processing Perspective Book
Cambridge University Press, CAMBRIDGE, 2010, ISBN: 9780521886598.
@book{<LineBreak> 11568_139116,
title = {Ontologies and the Lexicon. A Natural Language Processing Perspective},
author = {C. R. Huang and N. Calzolari and A. Gangemi and Alessandro Lenci and A. Oltramari and L. Prevot},
isbn = {9780521886598},
year = {2010},
date = {2010-01-01},
urldate = {2010-01-01},
publisher = {Cambridge University Press},
address = {CAMBRIDGE},
keywords = {},
pubstate = {published},
tppubtype = {book}
}
Zarcone, A.; Lenci, Alessandro
Event types in the mind and in the corpus Conference
Proceedings of Verb 2010 Interdisciplinary Workshop on Verb Features, Scuola Normale Superiore, 2010.
@conference{ 11568_141555,
title = {Event types in the mind and in the corpus},
author = {A. Zarcone and Alessandro Lenci},
year = {2010},
date = {2010-01-01},
booktitle = {Proceedings of Verb 2010 Interdisciplinary Workshop on Verb Features},
pages = {86–91},
publisher = {Scuola Normale Superiore},
abstract = {Event types (ET) have received consid- erable attention in formal semantics, but their importance in experimental linguis- tics has developed only recently. The aim of this work is to compare the perfor- mance of human annotators and corpus- based models in ET classification of Ital- ian verbs},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Event types (ET) have received consid- erable attention in formal semantics, but their importance in experimental linguis- tics has developed only recently. The aim of this work is to compare the perfor- mance of human annotators and corpus- based models in ET classification of Ital- ian verbs
Baroni, M.; Lenci, Alessandro
Distributional Memory: A General Framework for Corpus-Based Semantics Journal Article
In: COMPUTATIONAL LINGUISTICS, vol. 36, no. 4, pp. 673–721, 2010.
@article{ 11568_137140,
title = {Distributional Memory: A General Framework for Corpus-Based Semantics},
author = {M. Baroni and Alessandro Lenci},
url = {http://www.aclweb.org/anthology-new/J/J10/J10-4006.pdf},
year = {2010},
date = {2010-01-01},
journal = {COMPUTATIONAL LINGUISTICS},
volume = {36},
number = {4},
pages = {673–721},
abstract = {Research into corpus-based semantics has focused on the development of ad hoc models that treat single tasks, or sets of closely related tasks, as unrelated challenges to be tackled by extracting different kinds of distributional information from the corpus. As an alternative to this “one task, one model” approach, the Distributional Memory framework extracts distributional information once and for all from the corpus, in the form of a set of weighted word-link-word tuples arranged into a third-order tensor. Different matrices are then generated from the tensor, and their rows and columns constitute natural spaces to deal with different semantic problems. In this way, the same distributional information can be shared across tasks such as modeling word similarity judgments, discovering synonyms, concept categorization, predicting selectional preferences of verbs, solving analogy problems, classifying relations between word pairs, harvesting qualia structures with patterns or example pairs, predicting the typical properties of concepts, and classifying verbs into alternation classes. Extensive empirical testing in all these domains shows that a Distributional Memory implementation performs competitively against task-specific algorithms recently reported in the literature for the same tasks, and against our implementations of several state-of-the-art methods. The Distributional Memory approach is thus shown to be tenable despite the constraints imposed by its multi-purpose nature.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Research into corpus-based semantics has focused on the development of ad hoc models that treat single tasks, or sets of closely related tasks, as unrelated challenges to be tackled by extracting different kinds of distributional information from the corpus. As an alternative to this “one task, one model” approach, the Distributional Memory framework extracts distributional information once and for all from the corpus, in the form of a set of weighted word-link-word tuples arranged into a third-order tensor. Different matrices are then generated from the tensor, and their rows and columns constitute natural spaces to deal with different semantic problems. In this way, the same distributional information can be shared across tasks such as modeling word similarity judgments, discovering synonyms, concept categorization, predicting selectional preferences of verbs, solving analogy problems, classifying relations between word pairs, harvesting qualia structures with patterns or example pairs, predicting the typical properties of concepts, and classifying verbs into alternation classes. Extensive empirical testing in all these domains shows that a Distributional Memory implementation performs competitively against task-specific algorithms recently reported in the literature for the same tasks, and against our implementations of several state-of-the-art methods. The Distributional Memory approach is thus shown to be tenable despite the constraints imposed by its multi-purpose nature.
Bosco, C.; Montemagni, S.; Mazzei, A.; Lombardo, V.; Dell'Orletta, F.; Lenci, Alessandro; Lesmo, L.; Attardi, Giuseppe; Simi, Maria; Lavelli, A.; Hall, J.; Nilsson, J.; Nivre, J.
Comparing the Influence of Different Treebank Annotations on Dependency Parsing Performance Conference
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10), vol. 1, European Language Resources Association (ELRA), 2010, ISBN: 2951740867.
@conference{ 11568_198175,
title = {Comparing the Influence of Different Treebank Annotations on Dependency Parsing Performance},
author = {C. Bosco and S. Montemagni and A. Mazzei and V. Lombardo and F. Dell'Orletta and Alessandro Lenci and L. Lesmo and Giuseppe Attardi and Maria Simi and A. Lavelli and J. Hall and J. Nilsson and J. Nivre},
url = {http://www.lrec-conf.org/proceedings/lrec2010/pdf/196_Paper.pdf},
isbn = {2951740867},
year = {2010},
date = {2010-01-01},
booktitle = {Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)},
volume = {1},
pages = {1794–1801},
publisher = {European Language Resources Association (ELRA)},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Lenci, Alessandro; Johnson, Martina; Lapesa, G.
Building an Italian FrameNet through semi-automatic corpus analysis Conference
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10), 2010, ISBN: 2951740867.
@conference{ 11568_143937,
title = {Building an Italian FrameNet through semi-automatic corpus analysis},
author = {Alessandro Lenci and Martina Johnson and G. Lapesa},
url = {http://www.lrec-conf.org/proceedings/lrec2010/pdf/313_Paper.pdf},
isbn = {2951740867},
year = {2010},
date = {2010-01-01},
booktitle = {Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)},
pages = {12–19},
abstract = {In this paper, we outline the methodology we adopted to develop a FrameNet for Italian. The main element of novelty with respect to the original FrameNet is represented by the fact that the creation and annotation of Lexical Units is strictly grounded in distributional information (statistical distribution of verbal subcategorization frames, lexical and semantic preferences of each frame) automatically acquired from a large, dependency-parsed corpus. We claim that this approach allows us to overcome some of the shortcomings of the classical lexicographic method used to create FrameNet, by complementing the accuracy of manual annotation with the robustness of data on the global distributional patterns of a verb. In the paper, we describe our method for extracting distributional data from the corpus and the way we used it for the encoding and annotation of LUs. The long-term goal of our project is to create an electronic lexicon for Italian similar to the original English FrameNet. For the moment, we have developed a database of syntactic valences that will be made freely accessible via a web interface. This represents an autonomous resource besides the FrameNet lexicon, of which we have a beginning nucleus consisting of 791 annotated sentences.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
In this paper, we outline the methodology we adopted to develop a FrameNet for Italian. The main element of novelty with respect to the original FrameNet is represented by the fact that the creation and annotation of Lexical Units is strictly grounded in distributional information (statistical distribution of verbal subcategorization frames, lexical and semantic preferences of each frame) automatically acquired from a large, dependency-parsed corpus. We claim that this approach allows us to overcome some of the shortcomings of the classical lexicographic method used to create FrameNet, by complementing the accuracy of manual annotation with the robustness of data on the global distributional patterns of a verb. In the paper, we describe our method for extracting distributional data from the corpus and the way we used it for the encoding and annotation of LUs. The long-term goal of our project is to create an electronic lexicon for Italian similar to the original English FrameNet. For the moment, we have developed a database of syntactic valences that will be made freely accessible via a web interface. This represents an autonomous resource besides the FrameNet lexicon, of which we have a beginning nucleus consisting of 791 annotated sentences.
Poesio, M.; Baroni, M.; Lanz, O.; Lenci, Alessandro; Potamianos, A.; Schuetze, H.; WALDE, S. SCHULTE IM; Surian, L.
BabyExp: Constructing a huge multimodal resource to acquire commonsense knowledge like children do Conference
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10), 2010, ISBN: 2951740867.
@conference{ 11568_143117,
title = {BabyExp: Constructing a huge multimodal resource to acquire commonsense knowledge like children do},
author = {M. Poesio and M. Baroni and O. Lanz and Alessandro Lenci and A. Potamianos and H. Schuetze and S. SCHULTE IM WALDE and L. Surian},
url = {http://www.lrec-conf.org/proceedings/lrec2010/pdf/455_Paper.pdf},
isbn = {2951740867},
year = {2010},
date = {2010-01-01},
booktitle = {Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)},
pages = {3042–3048},
abstract = {The BabyExp project is collecting very dense audio and video recordings of the first 3 years of life of a baby. The corpus constructed in this way will be transcribed with automated techniques and made available to the research community. Moreover, techniques to extract commonsense conceptual knowledge incrementally from these multimodal data are also being explored within the project. The current paper describes BabyExp in general, and presents pilot studies on the feasability of the automated audio and video transcriptions.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
The BabyExp project is collecting very dense audio and video recordings of the first 3 years of life of a baby. The corpus constructed in this way will be transcribed with automated techniques and made available to the research community. Moreover, techniques to extract commonsense conceptual knowledge incrementally from these multimodal data are also being explored within the project. The current paper describes BabyExp in general, and presents pilot studies on the feasability of the automated audio and video transcriptions.
Attardi, Giuseppe; Dei, Rossi; Pietro, G. Di; Lenci, Alessandro; Montemagni, S.; Simi, Maria
A Resource and Tool for Super-sense Tagging of Italian Texts Conference
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10), European Language Resources Association (ELRA), 2010, ISBN: 2951740867.
@conference{ 11568_194270,
title = {A Resource and Tool for Super-sense Tagging of Italian Texts},
author = {Giuseppe Attardi and Rossi Dei and G. Di Pietro and Alessandro Lenci and S. Montemagni and Maria Simi},
url = {http://www.lrec-conf.org/proceedings/lrec2010/pdf/216_Paper.pdf},
isbn = {2951740867},
year = {2010},
date = {2010-01-01},
booktitle = {Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)},
pages = {2242–2248},
publisher = {European Language Resources Association (ELRA)},
abstract = {A SuperSense Tagger is a tool for the automatic analysis of texts that associates to each noun, verb, adjective and adverb a semantic category within a general taxonomy. The developed tagger, based on a statistical model (Maximum Entropy), required the creation of an Italian annotated corpus, to be used as a training set, and the improvement of various existing tools. The obtained results significantly improved the current state-of-the art for this particular task.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
A SuperSense Tagger is a tool for the automatic analysis of texts that associates to each noun, verb, adjective and adverb a semantic category within a general taxonomy. The developed tagger, based on a statistical model (Maximum Entropy), required the creation of an Italian annotated corpus, to be used as a training set, and the improvement of various existing tools. The obtained results significantly improved the current state-of-the art for this particular task.
2009
Lenci, Alessandro; Zarcone, A.
Un modello stocastico della classificazione azionale Conference
Atti del XL Congresso della Società di Linguistica Italiana (SLI), 2009, ISBN: 9788878704695.
@conference{ 11568_132962,
title = {Un modello stocastico della classificazione azionale},
author = {Alessandro Lenci and A. Zarcone},
isbn = {9788878704695},
year = {2009},
date = {2009-01-01},
booktitle = {Atti del XL Congresso della Società di Linguistica Italiana (SLI)},
pages = {125–148},
abstract = {Il fatto che uno stesso verbo possa avere valori azionali diversi a seconda del suo contesto linguistico solleva il problema di come modellare la complessa interazione dei fattori costituivi dell’Aktionsart. Per nessuna classe azionale sembra possibile selezionare un insieme di tratti la cui presenza in un contesto sia congiuntamente necessaria e sufficiente a garantire che l’evento venga interpretato come appartenente a quella particolare classe. Inoltre, gli stessi tipi azionali non si presentano come entità monolitiche, bensì come categorie che contengono rappresentanti verbali prototipici resistenti a variazioni contestuali, accanto invece a verbi che più facilmente danno luogo a fenomeni di polisemia a livello azionale. L’ipotesi di ricerca che esploriamo in questo lavoro è che l’interpretazione del valore azionale di un verbo in contesto possa essere modellata come il risultato di un complesso processo di integrazione di vincoli morfologici, sintattici e semantici di natura intrinsecamente probabilistica. Il peso relativo dei diversi vincoli viene stimato attraverso un algoritmo di apprendimento automatico basato sul principio della “massimizzazione dell’entropia”, che registra le correlazioni tra le classi azionali con diversi tratti del contesto linguistico dei verbi estratti da un corpus annotato.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Il fatto che uno stesso verbo possa avere valori azionali diversi a seconda del suo contesto linguistico solleva il problema di come modellare la complessa interazione dei fattori costituivi dell’Aktionsart. Per nessuna classe azionale sembra possibile selezionare un insieme di tratti la cui presenza in un contesto sia congiuntamente necessaria e sufficiente a garantire che l’evento venga interpretato come appartenente a quella particolare classe. Inoltre, gli stessi tipi azionali non si presentano come entità monolitiche, bensì come categorie che contengono rappresentanti verbali prototipici resistenti a variazioni contestuali, accanto invece a verbi che più facilmente danno luogo a fenomeni di polisemia a livello azionale. L’ipotesi di ricerca che esploriamo in questo lavoro è che l’interpretazione del valore azionale di un verbo in contesto possa essere modellata come il risultato di un complesso processo di integrazione di vincoli morfologici, sintattici e semantici di natura intrinsecamente probabilistica. Il peso relativo dei diversi vincoli viene stimato attraverso un algoritmo di apprendimento automatico basato sul principio della “massimizzazione dell’entropia”, che registra le correlazioni tra le classi azionali con diversi tratti del contesto linguistico dei verbi estratti da un corpus annotato.
Dell'Orletta, F.; Lenci, Alessandro; Marchi, S.; Montemagni, S.; Pirrelli, V.
Text-2-Knowledge: una piattaforma linguistico-computazionale per l’estrazione di conoscenza da testi Conference
Atti del XL Congresso della Società di Linguistica Italiana (SLI), 2009, ISBN: 9788878704695.
@conference{ 11568_129151,
title = {Text-2-Knowledge: una piattaforma linguistico-computazionale per l’estrazione di conoscenza da testi},
author = {F. Dell'Orletta and Alessandro Lenci and S. Marchi and S. Montemagni and V. Pirrelli},
isbn = {9788878704695},
year = {2009},
date = {2009-01-01},
booktitle = {Atti del XL Congresso della Società di Linguistica Italiana (SLI)},
pages = {285–300},
abstract = {In questo contributo presentiamo Text-2-Knowledge (T2K), una piattaforma software sviluppata congiuntamente dall’Istituto di Linguistica Computazionale (CNR) e dal Dipartimento di Linguistica dell’Università di Pisa per l’acquisizione di tipi diversi di informazione semantico-lessicale da documenti testuali. Attraverso l’uso combinato di tecniche statistiche e di strumenti avanzati per il TAL, T2K è in grado di analizzare il contenuto linguistico dei documenti, individuare i termini potenzialmente più significativi, ricostruire una “mappa” multidimensionale dei concetti espressi da questi termini, sviluppare un’ontologia del dominio di interesse. Per scopi espositivi, il funzionamento di T2K sarà illustrato con i risultati di esperimenti di estrazione e strutturazione di terminologia metalinguistica condotti su un corpus di testi del settore della Linguistica Computazionale.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
In questo contributo presentiamo Text-2-Knowledge (T2K), una piattaforma software sviluppata congiuntamente dall’Istituto di Linguistica Computazionale (CNR) e dal Dipartimento di Linguistica dell’Università di Pisa per l’acquisizione di tipi diversi di informazione semantico-lessicale da documenti testuali. Attraverso l’uso combinato di tecniche statistiche e di strumenti avanzati per il TAL, T2K è in grado di analizzare il contenuto linguistico dei documenti, individuare i termini potenzialmente più significativi, ricostruire una “mappa” multidimensionale dei concetti espressi da questi termini, sviluppare un’ontologia del dominio di interesse. Per scopi espositivi, il funzionamento di T2K sarà illustrato con i risultati di esperimenti di estrazione e strutturazione di terminologia metalinguistica condotti su un corpus di testi del settore della Linguistica Computazionale.
Lenci, Alessandro
Spazi di parole: metafore e rappresentazioni semantiche Journal Article
In: PARADIGMI, vol. 27, no. 1, pp. 83–100, 2009.
@article{ 11568_132891,
title = {Spazi di parole: metafore e rappresentazioni semantiche},
author = {Alessandro Lenci},
year = {2009},
date = {2009-01-01},
journal = {PARADIGMI},
volume = {27},
number = {1},
pages = {83–100},
abstract = {L’obiettivo di questo contributo è l’analisi critica dell’analogia del lessico come spazio di parole nella sua natura di metafora scientifica che definisce il significato lessicale attraverso una rete di rapporti topologici tra parole, determinati dalle loro modalità di co-occorrenza a livello sintagmatico. La metafora costitutiva dei modelli semantici distribuzionali può essere ricondotta – usando la terminologia di Lakoff e Johnson (1980) – allo schema astratto SIGNIFICATO = SPAZIO DI PAROLE. La struttura e i modi di rappresentare matematicamente lo spazio sono infatti scelti come “dominio sorgente” (source domain) nei cui termini vengono rappresentati e modellati i significati dei termini lessicali. Analizzare il contributo effettivo offerto da questa metafora implica indagare l’organizzazione del “dominio sorgente” – in questo caso la nozione di spazio e la sua struttura –, i principi della sua proiezione sul “dominio obiettivo” (target domain) – il significato lessicale appunto – e le conseguenze che questa proiezione comporta nel modo di concepire le stesse rappresentazioni semantiche. Non si tratta, dunque, solo di una riflessione sul particolare metalinguaggio adottato da alcuni modelli semantici. Data la sua natura costitutiva, l’analisi della metafora del lessico come spazio di parole ci conduce direttamente ad affrontare il tema della sua forza esplicativa rispetto al dominio che essa intende rappresentare, ovvero della sua validità come modello del significato. Sebbene questo lavoro non si proponga di offrire una discussione delle teorie della metafora, tuttavia uno dei criteri con cui valuteremo il valore costitutivo dell’analogia dello spazio di parole sarà proprio rispetto alla sua capacità di offrire un modo alternativo di modellare le rappresentazioni semantiche, in grado di aprire interessanti prospettive per affrontare il problema stesso del linguaggio metaforico e delle dinamiche del significato lessicale.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
L’obiettivo di questo contributo è l’analisi critica dell’analogia del lessico come spazio di parole nella sua natura di metafora scientifica che definisce il significato lessicale attraverso una rete di rapporti topologici tra parole, determinati dalle loro modalità di co-occorrenza a livello sintagmatico. La metafora costitutiva dei modelli semantici distribuzionali può essere ricondotta – usando la terminologia di Lakoff e Johnson (1980) – allo schema astratto SIGNIFICATO = SPAZIO DI PAROLE. La struttura e i modi di rappresentare matematicamente lo spazio sono infatti scelti come “dominio sorgente” (source domain) nei cui termini vengono rappresentati e modellati i significati dei termini lessicali. Analizzare il contributo effettivo offerto da questa metafora implica indagare l’organizzazione del “dominio sorgente” – in questo caso la nozione di spazio e la sua struttura –, i principi della sua proiezione sul “dominio obiettivo” (target domain) – il significato lessicale appunto – e le conseguenze che questa proiezione comporta nel modo di concepire le stesse rappresentazioni semantiche. Non si tratta, dunque, solo di una riflessione sul particolare metalinguaggio adottato da alcuni modelli semantici. Data la sua natura costitutiva, l’analisi della metafora del lessico come spazio di parole ci conduce direttamente ad affrontare il tema della sua forza esplicativa rispetto al dominio che essa intende rappresentare, ovvero della sua validità come modello del significato. Sebbene questo lavoro non si proponga di offrire una discussione delle teorie della metafora, tuttavia uno dei criteri con cui valuteremo il valore costitutivo dell’analogia dello spazio di parole sarà proprio rispetto alla sua capacità di offrire un modo alternativo di modellare le rappresentazioni semantiche, in grado di aprire interessanti prospettive per affrontare il problema stesso del linguaggio metaforico e delle dinamiche del significato lessicale.
Baroni, M.; Lenci, Alessandro
One semantic memory, many semantic tasks Conference
Proceedings of the EACL Workshop on GEometrical Models of Natural Language Semantics, 2009.
@conference{ 11568_128263,
title = {One semantic memory, many semantic tasks},
author = {M. Baroni and Alessandro Lenci},
url = {http://aclweb.org/anthology/W/W09/W09-0201.pdf},
year = {2009},
date = {2009-01-01},
booktitle = {Proceedings of the EACL Workshop on GEometrical Models of Natural Language Semantics},
abstract = {We propose an approach to corpus-based semantics, inspired by cognitive science, in which different semantic tasks are tackled using the same underlying repository of distributional information, collected once and for all from the source corpus. Task-specific semantic spaces are then built on demand from the repository. A straightforward implementation of our proposal achieves state-of-the-art performance on a number of unrelated tasks.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
We propose an approach to corpus-based semantics, inspired by cognitive science, in which different semantic tasks are tackled using the same underlying repository of distributional information, collected once and for all from the source corpus. Task-specific semantic spaces are then built on demand from the repository. A straightforward implementation of our proposal achieves state-of-the-art performance on a number of unrelated tasks.
Bertinetto, P. M.; Lenci, Alessandro; Noccetti, Sabrina
Metodi quantitativi nell’analisi dell’acquisizione delle strutture tempo-aspettuali Conference
Atti del XL Congresso della Società di Linguistica Italiana (SLI), 2009, ISBN: 9788878704695.
@conference{ 11568_135502,
title = {Metodi quantitativi nell’analisi dell’acquisizione delle strutture tempo-aspettuali},
author = {P. M. Bertinetto and Alessandro Lenci and Sabrina Noccetti},
isbn = {9788878704695},
year = {2009},
date = {2009-01-01},
booktitle = {Atti del XL Congresso della Società di Linguistica Italiana (SLI)},
pages = {97–123},
abstract = {In questo lavoro, ci concentriamo in modo particolare sui risultati concernenti la semantica e morfologia verbale. I dati etichettati sono stati sottoposti a due tipi di analisi:
1. un’analisi estensiva di carattere statistico, mirante a far emergere le correlazioni tra le diverse categorie semantiche (sul piano del tempo, dell’aspetto e dell’azionalità) e le categorie morfologiche via via acquisite dai tre apprendenti, ovviamente in rapporto al comportamento degli adulti interagenti.
2. un’analisi computazionale condotta sui verbi più frequenti per ciascuna classe azionale attraverso l’applicazione di Multi-dimensional Scaling (MDS) e Self-Organizing Maps (SOMs) (Kohonen 1997). Attraverso il MDS è possibile ottenere una visione sinottica delle modalità secondo le quali verbi appartenenti a classi azionali diverse si dispongono in uno spazio multidimensionale di variabili quantitative, che registrano distribuzioni di tratti morfologici e sintattici. Le SOMs sono un modello neurale non-supervisionato, che consente invece di simulare il processo dinamico di formazione di proto-classi azionali che emergono dalle correlazioni statistiche presenti nell’input linguistico.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
In questo lavoro, ci concentriamo in modo particolare sui risultati concernenti la semantica e morfologia verbale. I dati etichettati sono stati sottoposti a due tipi di analisi:
1. un’analisi estensiva di carattere statistico, mirante a far emergere le correlazioni tra le diverse categorie semantiche (sul piano del tempo, dell’aspetto e dell’azionalità) e le categorie morfologiche via via acquisite dai tre apprendenti, ovviamente in rapporto al comportamento degli adulti interagenti.
2. un’analisi computazionale condotta sui verbi più frequenti per ciascuna classe azionale attraverso l’applicazione di Multi-dimensional Scaling (MDS) e Self-Organizing Maps (SOMs) (Kohonen 1997). Attraverso il MDS è possibile ottenere una visione sinottica delle modalità secondo le quali verbi appartenenti a classi azionali diverse si dispongono in uno spazio multidimensionale di variabili quantitative, che registrano distribuzioni di tratti morfologici e sintattici. Le SOMs sono un modello neurale non-supervisionato, che consente invece di simulare il processo dinamico di formazione di proto-classi azionali che emergono dalle correlazioni statistiche presenti nell’input linguistico.
1. un’analisi estensiva di carattere statistico, mirante a far emergere le correlazioni tra le diverse categorie semantiche (sul piano del tempo, dell’aspetto e dell’azionalità) e le categorie morfologiche via via acquisite dai tre apprendenti, ovviamente in rapporto al comportamento degli adulti interagenti.
2. un’analisi computazionale condotta sui verbi più frequenti per ciascuna classe azionale attraverso l’applicazione di Multi-dimensional Scaling (MDS) e Self-Organizing Maps (SOMs) (Kohonen 1997). Attraverso il MDS è possibile ottenere una visione sinottica delle modalità secondo le quali verbi appartenenti a classi azionali diverse si dispongono in uno spazio multidimensionale di variabili quantitative, che registrano distribuzioni di tratti morfologici e sintattici. Le SOMs sono un modello neurale non-supervisionato, che consente invece di simulare il processo dinamico di formazione di proto-classi azionali che emergono dalle correlazioni statistiche presenti nell’input linguistico.
Bertinetto, Piermarco; Lenci, Alessandro; Noccetti, Sabrina; Agonici, Maddalena
Metodi quantitativi nello studio dell’acquisizione delle strutture tempo-aspettuali Book Chapter
In: Linguistica e Modelli tecnologici di ricerca, pp. 97–123, Bulzoni Editore, ROMA, 2009, ISBN: 9788878704695.
@inbook{ 11568_127457,
title = {Metodi quantitativi nello studio dell’acquisizione delle strutture tempo-aspettuali},
author = {Piermarco Bertinetto and Alessandro Lenci and Sabrina Noccetti and Maddalena Agonici},
isbn = {9788878704695},
year = {2009},
date = {2009-01-01},
booktitle = {Linguistica e Modelli tecnologici di ricerca},
pages = {97–123},
publisher = {Bulzoni Editore},
address = {ROMA},
abstract = {La concezione prevalente riguardo all'acquisizione delle strutture tempo-aspetuali prevede che esse siano innescate (o mediate) da categorie azionali, di cui gli apprendenti avrebbero una conoscenza intuitiva.
Questo contributo propone invece l'ipotesi che nelle grammatiche iniziali non ci sia alcuna conoscenza circa le strutture della grammatica tempo-aspettuale, la cui costruzione è mediata dall'input adulto o dala morfologia della lingua target. La costruzione delle categorie tempo-aspettuali si compie, quindi, a partire da categorie che non sembrano avere un autentico "ruolo-guida". Queste conclusioni sono rafforzate dalle due diverse metodologie di analisi dei dati: quella statistica e multidimensionale.},
keywords = {},
pubstate = {published},
tppubtype = {inbook}
}
La concezione prevalente riguardo all'acquisizione delle strutture tempo-aspetuali prevede che esse siano innescate (o mediate) da categorie azionali, di cui gli apprendenti avrebbero una conoscenza intuitiva.
Questo contributo propone invece l'ipotesi che nelle grammatiche iniziali non ci sia alcuna conoscenza circa le strutture della grammatica tempo-aspettuale, la cui costruzione è mediata dall'input adulto o dala morfologia della lingua target. La costruzione delle categorie tempo-aspettuali si compie, quindi, a partire da categorie che non sembrano avere un autentico "ruolo-guida". Queste conclusioni sono rafforzate dalle due diverse metodologie di analisi dei dati: quella statistica e multidimensionale.
Questo contributo propone invece l'ipotesi che nelle grammatiche iniziali non ci sia alcuna conoscenza circa le strutture della grammatica tempo-aspettuale, la cui costruzione è mediata dall'input adulto o dala morfologia della lingua target. La costruzione delle categorie tempo-aspettuali si compie, quindi, a partire da categorie che non sembrano avere un autentico "ruolo-guida". Queste conclusioni sono rafforzate dalle due diverse metodologie di analisi dei dati: quella statistica e multidimensionale.
Lenci, Alessandro; Sandu, G.
Logic and linguistics in the twentieth century Book Chapter
In: The Development of Modern Logic, pp. 775–847, Oxford University Press, OXFORD, 2009, ISBN: 9780195137316.
@inbook{ 11568_133075,
title = {Logic and linguistics in the twentieth century},
author = {Alessandro Lenci and G. Sandu},
isbn = {9780195137316},
year = {2009},
date = {2009-01-01},
booktitle = {The Development of Modern Logic},
pages = {775–847},
publisher = {Oxford University Press},
address = {OXFORD},
abstract = {The interaction between logic and linguistics on the nature of universal grammar can be roughly divided into three phases, which will be analysed in details in the next sections. The first phase (beginning of the century up to the 1960s) was characterized by an extremely intense work in the field of logical grammar (§. 2), with the arising of categorial grammar within the Polish School in the first decades of the century and its extensive application to ordinary language by Yehoshua Bar-Hillel in the early 1950s. Besides, the work on truth-conditional semantics by Tarsky, Quine and Davidson (§. 3) provided the necessary background to the model-theoretic analyses of natural language and to Montague Grammar in the 1970s. On the linguistics side, in 1957 the transformational generative paradigm made its first steps out of the banks of American post-Bloomfieldian structuralism and behaviourism (§. 4). Chomsky's critique of the inadequacies of phrase structure grammars had a strong impact on the tradition of logical grammar, by revealing the limits and problems of categorial models. Moreover, in these years the generative architecture of the universal grammar received its first shaping, accompanied by the initial steps of the debate on the role and nature of semantic theory.
The second phase (late 1960s, throughout the 1970s) began with the crisis of the semantic models developed in the early period of generative grammar and the rise and fall of the Generative Semantics enterprise (§. 5). One of the major events of this period was the explosion of Montague Grammar and the subsequent breakthrough made in the linguistic community by the development of model-theoretic semantics (§. 6). More generally, these years were characterized by a great debate on the proper position of semantics with the theory of grammar, and by the first attempts of carrying out extensive comparisons and integrations between generative linguistics and logical grammar.
The third phase (starting from the beginning of the 1980s) is best illustrated by referring to the central role acquired in the Government and Binding version of Chomsky's theory by the notion of Logical Form (LF) (§. 7), resulting in an intense work in linguistics on topics like quantification, coreference, etc., with the consequent constant readjustment of the border between logic and formal linguistics.},
keywords = {},
pubstate = {published},
tppubtype = {inbook}
}
The interaction between logic and linguistics on the nature of universal grammar can be roughly divided into three phases, which will be analysed in details in the next sections. The first phase (beginning of the century up to the 1960s) was characterized by an extremely intense work in the field of logical grammar (§. 2), with the arising of categorial grammar within the Polish School in the first decades of the century and its extensive application to ordinary language by Yehoshua Bar-Hillel in the early 1950s. Besides, the work on truth-conditional semantics by Tarsky, Quine and Davidson (§. 3) provided the necessary background to the model-theoretic analyses of natural language and to Montague Grammar in the 1970s. On the linguistics side, in 1957 the transformational generative paradigm made its first steps out of the banks of American post-Bloomfieldian structuralism and behaviourism (§. 4). Chomsky's critique of the inadequacies of phrase structure grammars had a strong impact on the tradition of logical grammar, by revealing the limits and problems of categorial models. Moreover, in these years the generative architecture of the universal grammar received its first shaping, accompanied by the initial steps of the debate on the role and nature of semantic theory.
The second phase (late 1960s, throughout the 1970s) began with the crisis of the semantic models developed in the early period of generative grammar and the rise and fall of the Generative Semantics enterprise (§. 5). One of the major events of this period was the explosion of Montague Grammar and the subsequent breakthrough made in the linguistic community by the development of model-theoretic semantics (§. 6). More generally, these years were characterized by a great debate on the proper position of semantics with the theory of grammar, and by the first attempts of carrying out extensive comparisons and integrations between generative linguistics and logical grammar.
The third phase (starting from the beginning of the 1980s) is best illustrated by referring to the central role acquired in the Government and Binding version of Chomsky's theory by the notion of Logical Form (LF) (§. 7), resulting in an intense work in linguistics on topics like quantification, coreference, etc., with the consequent constant readjustment of the border between logic and formal linguistics.
The second phase (late 1960s, throughout the 1970s) began with the crisis of the semantic models developed in the early period of generative grammar and the rise and fall of the Generative Semantics enterprise (§. 5). One of the major events of this period was the explosion of Montague Grammar and the subsequent breakthrough made in the linguistic community by the development of model-theoretic semantics (§. 6). More generally, these years were characterized by a great debate on the proper position of semantics with the theory of grammar, and by the first attempts of carrying out extensive comparisons and integrations between generative linguistics and logical grammar.
The third phase (starting from the beginning of the 1980s) is best illustrated by referring to the central role acquired in the Government and Binding version of Chomsky's theory by the notion of Logical Form (LF) (§. 7), resulting in an intense work in linguistics on topics like quantification, coreference, etc., with the consequent constant readjustment of the border between logic and formal linguistics.
Lenci, Alessandro; Montemagni, S.; Pirrelli, V.
Annotazione sintattica di corpora: aspetti metodologici Book Chapter
In: Corpora di italiano L2: tecnologie, metodi, spunti teorici, pp. 25–46, Guerra Edizioni, PERUGIA, 2009, ISBN: 9788855701686.
@inbook{ 11568_133077,
title = {Annotazione sintattica di corpora: aspetti metodologici},
author = {Alessandro Lenci and S. Montemagni and V. Pirrelli},
isbn = {9788855701686},
year = {2009},
date = {2009-01-01},
booktitle = {Corpora di italiano L2: tecnologie, metodi, spunti teorici},
pages = {25–46},
publisher = {Guerra Edizioni},
address = {PERUGIA},
abstract = {Un assunto sempre più condiviso nell’ambito degli studi sull’acquisizione sia di L1 che di L2 è che l’evidenza empirica privilegiata debba essere rappresentata da corpora di produzioni scritte o orali degli apprendenti, estensivamente annotate a molteplici livelli di rappresentazione linguistica. Più in generale, corpora lemmatizzati e annotati a livello morfosintattico fanno ormai parte dello strumentario comune del linguista. Accanto ad essi, si fa però strada l’esigenza di disporre di risorse testuali più sofisticate dal punto di vista delle modalità di esplorazione linguistica, come ad esempio corpora annotati a livello sintattico (le cosiddette treebank). Questi consentono infatti di osservare i processi di convergenza degli apprendenti verso la lingua “obiettivo” anche a livello di specifici tratti grammaticali astratti o di macro-strutture linguistiche.},
keywords = {},
pubstate = {published},
tppubtype = {inbook}
}
Un assunto sempre più condiviso nell’ambito degli studi sull’acquisizione sia di L1 che di L2 è che l’evidenza empirica privilegiata debba essere rappresentata da corpora di produzioni scritte o orali degli apprendenti, estensivamente annotate a molteplici livelli di rappresentazione linguistica. Più in generale, corpora lemmatizzati e annotati a livello morfosintattico fanno ormai parte dello strumentario comune del linguista. Accanto ad essi, si fa però strada l’esigenza di disporre di risorse testuali più sofisticate dal punto di vista delle modalità di esplorazione linguistica, come ad esempio corpora annotati a livello sintattico (le cosiddette treebank). Questi consentono infatti di osservare i processi di convergenza degli apprendenti verso la lingua “obiettivo” anche a livello di specifici tratti grammaticali astratti o di macro-strutture linguistiche.
2008
Lenci, Alessandro; Mcgillivray, B.; Montemagni, S.; Pirrelli, V.
Unsupervised Acquisition of Verb Subcategorization Frames from Shallow-Parsed Corpora Conference
Proceedings of LREC 2008, 2008, ISBN: 2951740840.
@conference{ 11568_119626,
title = {Unsupervised Acquisition of Verb Subcategorization Frames from Shallow-Parsed Corpora},
author = {Alessandro Lenci and B. Mcgillivray and S. Montemagni and V. Pirrelli},
url = {http://www.lrec-conf.org/proceedings/lrec2008/pdf/763_paper.pdf},
isbn = {2951740840},
year = {2008},
date = {2008-01-01},
booktitle = {Proceedings of LREC 2008},
pages = {3000–3006},
abstract = {In this paper, we reported experiments of unsupervised automatic acquisition of Italian and English verb subcategorization frames (SCFs) from general and domain corpora. The proposed technique operates on syntactically shallow-parsed corpora on the basis of a limited number of search heuristics not relying on any previous lexico-syntactic knowledge about SCFs. Although preliminary, reported results are in line with state-of-the-art lexical acquisition systems. The issue of whether verbs sharing similar SCFs distributions happen to share similar semantic properties as well was also explored by clustering verbs that share frames with the same distribution using the Minimum Description Length Principle (MDL). First experiments in this direction were carried out on Italian verbs with encouraging results.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
In this paper, we reported experiments of unsupervised automatic acquisition of Italian and English verb subcategorization frames (SCFs) from general and domain corpora. The proposed technique operates on syntactically shallow-parsed corpora on the basis of a limited number of search heuristics not relying on any previous lexico-syntactic knowledge about SCFs. Although preliminary, reported results are in line with state-of-the-art lexical acquisition systems. The issue of whether verbs sharing similar SCFs distributions happen to share similar semantic properties as well was also explored by clustering verbs that share frames with the same distribution using the Minimum Description Length Principle (MDL). First experiments in this direction were carried out on Italian verbs with encouraging results.
Bertinetto, P. M.; Lenci, Alessandro; Noccetti, Sabrina; Agonigi, M.
The indispensable complexity (When harder is easier) Book Chapter
In: Threads in the Complex Fabric of Language, vol. 1, pp. 37–51, Felici Editore, GHEZZANO, 2008, ISBN: 9788860192257.
@inbook{ 11568_123679,
title = {The indispensable complexity (When harder is easier)},
author = {P. M. Bertinetto and Alessandro Lenci and Sabrina Noccetti and M. Agonigi},
isbn = {9788860192257},
year = {2008},
date = {2008-01-01},
booktitle = {Threads in the Complex Fabric of Language},
volume = {1},
pages = {37–51},
publisher = {Felici Editore},
address = {GHEZZANO},
abstract = {COMPLEXITY has become a key notion in EMERGENTIST approaches to language and cognitive development, namely, the approaches adhering to a functionalist, anti-modular and anti-innatist paradigm. In this context, “complexity” must be clearly stripped of any prima facie negative connotation: being “complex” is not necessarily the same as being “complicated or difficult”. Rather, it should be interpreted within terms of dynamic systems theory, as a way to characterize the particular level of language organization and its specific dynamics. Indeed, an important hallmark of language as a complex system is the deep interplay between lexical and grammatical development, which gives rise to various types of non-linear dynamics in language ontogenesis. The role of complexity in language acquisition can also be clearly observed in the formation of the actionality-temporality-aspect-mood (ATAM) system, where grammar and lexicon development, cognitive maturation and language acquisition appear to be deeply intertwined.},
keywords = {},
pubstate = {published},
tppubtype = {inbook}
}
COMPLEXITY has become a key notion in EMERGENTIST approaches to language and cognitive development, namely, the approaches adhering to a functionalist, anti-modular and anti-innatist paradigm. In this context, “complexity” must be clearly stripped of any prima facie negative connotation: being “complex” is not necessarily the same as being “complicated or difficult”. Rather, it should be interpreted within terms of dynamic systems theory, as a way to characterize the particular level of language organization and its specific dynamics. Indeed, an important hallmark of language as a complex system is the deep interplay between lexical and grammatical development, which gives rise to various types of non-linear dynamics in language ontogenesis. The role of complexity in language acquisition can also be clearly observed in the formation of the actionality-temporality-aspect-mood (ATAM) system, where grammar and lexicon development, cognitive maturation and language acquisition appear to be deeply intertwined.
Bertinetto, P. M.; Lenci, Alessandro; Noccetti, Sabrina; Agonigi, M.
The Indispensable Complexity (When Harder is Easier). Lexical and Grammatical Expansion in three Italian L1 Learners Book Chapter
In: Threads in the Complex Fabric of Language. Linguistic and Literary Studies in Honour of Lavinia Merlini Barbaresi, Felici Editore, GHEZZANO, 2008, ISBN: 9788860192257.
@inbook{ 11568_119362,
title = {The Indispensable Complexity (When Harder is Easier). Lexical and Grammatical Expansion in three Italian L1 Learners},
author = {P. M. Bertinetto and Alessandro Lenci and Sabrina Noccetti and M. Agonigi},
isbn = {9788860192257},
year = {2008},
date = {2008-01-01},
booktitle = {Threads in the Complex Fabric of Language. Linguistic and Literary Studies in Honour of Lavinia Merlini Barbaresi},
publisher = {Felici Editore},
address = {GHEZZANO},
abstract = {COMPLEXITY has become a key notion in EMERGENTIST approaches to language
and cognitive development (MacWhinney 1999), namely, the approaches adhering to a
functionalist, anti-modular and anti-innatist paradigm. In this context, “complexity” must
be clearly stripped of any prima facie negative connotation: being “complex” is not
necessarily the same as being “complicated or difficult” (Merlini Barbaresi 2003).
Rather, it should be interpreted within terms of dynamic systems theory, as a way to
characterize the particular level of language organization and its specific dynamics.
Indeed, an important hallmark of language as a complex system is the deep interplay
between lexical and grammatical development, which gives rise to various types of nonlinear
dynamics in language ontogenesis. The role of complexity in language acquisition
can also be clearly observed in the formation of the actionality-temporality-aspect-mood
(ATAM) system, where grammar and lexicon development, cognitive maturation and
language acquisition appear to be deeply intertwined.},
keywords = {},
pubstate = {published},
tppubtype = {inbook}
}
COMPLEXITY has become a key notion in EMERGENTIST approaches to language
and cognitive development (MacWhinney 1999), namely, the approaches adhering to a
functionalist, anti-modular and anti-innatist paradigm. In this context, “complexity” must
be clearly stripped of any prima facie negative connotation: being “complex” is not
necessarily the same as being “complicated or difficult” (Merlini Barbaresi 2003).
Rather, it should be interpreted within terms of dynamic systems theory, as a way to
characterize the particular level of language organization and its specific dynamics.
Indeed, an important hallmark of language as a complex system is the deep interplay
between lexical and grammatical development, which gives rise to various types of nonlinear
dynamics in language ontogenesis. The role of complexity in language acquisition
can also be clearly observed in the formation of the actionality-temporality-aspect-mood
(ATAM) system, where grammar and lexicon development, cognitive maturation and
language acquisition appear to be deeply intertwined.
and cognitive development (MacWhinney 1999), namely, the approaches adhering to a
functionalist, anti-modular and anti-innatist paradigm. In this context, “complexity” must
be clearly stripped of any prima facie negative connotation: being “complex” is not
necessarily the same as being “complicated or difficult” (Merlini Barbaresi 2003).
Rather, it should be interpreted within terms of dynamic systems theory, as a way to
characterize the particular level of language organization and its specific dynamics.
Indeed, an important hallmark of language as a complex system is the deep interplay
between lexical and grammatical development, which gives rise to various types of nonlinear
dynamics in language ontogenesis. The role of complexity in language acquisition
can also be clearly observed in the formation of the actionality-temporality-aspect-mood
(ATAM) system, where grammar and lexicon development, cognitive maturation and
language acquisition appear to be deeply intertwined.
Baroni, M.; Lenci, Alessandro; Murphy, M.; Poesio, M.
Modelling Semantic Property Acquisition from Single Linguistic Exposure Conference
Proceedings of the 4th Workshop on Psychocomputational Models of Human Language Acquisition, in conjunction with the 30th Annual Meeting of the Cognitive Science Society, 2008, ISBN: 9780976831846.
@conference{ 11568_124411,
title = {Modelling Semantic Property Acquisition from Single Linguistic Exposure},
author = {M. Baroni and Alessandro Lenci and M. Murphy and M. Poesio},
isbn = {9780976831846},
year = {2008},
date = {2008-01-01},
booktitle = {Proceedings of the 4th Workshop on Psychocomputational Models of Human Language Acquisition, in conjunction with the 30th Annual Meeting of the Cognitive Science Society},
pages = {21–22},
abstract = {Linguistic structures are a key information source in semantic knowledge acquisition. Indeed,
both adults and children (Bloom, 2000) can learn a new property of a known or unknown concept
from a single linguistic exposure. We formalize this as the ability to 1) decide whether the
structure encountered expresses a property relevant to the concept (“oomparumpuses have tails”
is likely relevant, while “that oomparumpus is hungry” may not be); 2) assign a type to properties
deemed relevant (tails are parts, while being a bird describes class membership). We investigate,
computationally, to what extent a single exposure to a concept-property pair in linguistic context
is sufficient for effective learning, and what prior knowledge makes this possible.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Linguistic structures are a key information source in semantic knowledge acquisition. Indeed,
both adults and children (Bloom, 2000) can learn a new property of a known or unknown concept
from a single linguistic exposure. We formalize this as the ability to 1) decide whether the
structure encountered expresses a property relevant to the concept (“oomparumpuses have tails”
is likely relevant, while “that oomparumpus is hungry” may not be); 2) assign a type to properties
deemed relevant (tails are parts, while being a bird describes class membership). We investigate,
computationally, to what extent a single exposure to a concept-property pair in linguistic context
is sufficient for effective learning, and what prior knowledge makes this possible.
both adults and children (Bloom, 2000) can learn a new property of a known or unknown concept
from a single linguistic exposure. We formalize this as the ability to 1) decide whether the
structure encountered expresses a property relevant to the concept (“oomparumpuses have tails”
is likely relevant, while “that oomparumpus is hungry” may not be); 2) assign a type to properties
deemed relevant (tails are parts, while being a bird describes class membership). We investigate,
computationally, to what extent a single exposure to a concept-property pair in linguistic context
is sufficient for effective learning, and what prior knowledge makes this possible.
Lenci, Alessandro
L'autonomia del linguistico Conference
Atti del Convegno 2008 del CODISCO, Corisco, 2008, ISBN: 9788888325156.
@conference{ 11568_119627,
title = {L'autonomia del linguistico},
author = {Alessandro Lenci},
isbn = {9788888325156},
year = {2008},
date = {2008-01-01},
booktitle = {Atti del Convegno 2008 del CODISCO},
pages = {135–145},
publisher = {Corisco},
abstract = {Cosa significa affermare che il linguaggio è autonomo? Un primo modo di interpretare questa domanda è nel senso dell’esistenza di una “facoltà del linguaggio” intesa come un insieme di principi deputati a regolare l’organizzazione delle sue strutture rappresentazionali e le dinamiche del loro apprendimento, principi che sono “linguaggio-specifici” e qualitativamente diversi rispetto a quelli che ritroviamo in altri moduli cognitivi. Potremmo definire questo il senso “classico” e “forte” di autonomia, che ritroviamo secondo modulazioni diverse nei vari percorsi della linguistica di ispirazione chomskiana. In tale prospettiva, la facoltà del linguaggio è autonoma in quanto “speciale” rispetto ad altri moduli della cognizione, ad esempio in quanto fondata sulla capacità di generare e manipolare strutture simboliche ricorsive. La “narrow syntax” di Hauser et al. (2002) sembra puntare esattamente in questa direzione, ovvero verso l’esistenza di un nucleo autonomamente “linguistico” della cognizione che, pur interfacciandosi con i moduli cognitivi deputati all’organizzazione concettuale o all’elaborazione dell’informazione sensomotoria, ad essi non è comunque riducibile, poiché obbedisce a vincoli che le sono propri. Questi non sono interpretabili in senso puramente funzionalistico, in quanto sono virtualmente non spiegabili (ontogeneticamente e filogeneticamente) con le funzioni comunicative per le quali le strutture sono usate (Jackendoff e Pinker (2005) ad esempio criticano Hauser et al. (2002) proprio su questo punto, ovvero per il loro rifiuto di concepire il linguaggio come un prodotto dell’adattamento in funzione della comunicazione). Secondo l’accezione chomskiana di autonomia, i meccanismi stessi di apprendimento del linguaggio sono speciali e comunque non riducibili a principi generali di astrazione induttiva dal dato fattuale: la facoltà del linguaggio contiene invece elementi a priori che le sono propri e che guidano la maturazione delle strutture che essa si trova a governare nella competenza linguistica del parlante adulto.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Cosa significa affermare che il linguaggio è autonomo? Un primo modo di interpretare questa domanda è nel senso dell’esistenza di una “facoltà del linguaggio” intesa come un insieme di principi deputati a regolare l’organizzazione delle sue strutture rappresentazionali e le dinamiche del loro apprendimento, principi che sono “linguaggio-specifici” e qualitativamente diversi rispetto a quelli che ritroviamo in altri moduli cognitivi. Potremmo definire questo il senso “classico” e “forte” di autonomia, che ritroviamo secondo modulazioni diverse nei vari percorsi della linguistica di ispirazione chomskiana. In tale prospettiva, la facoltà del linguaggio è autonoma in quanto “speciale” rispetto ad altri moduli della cognizione, ad esempio in quanto fondata sulla capacità di generare e manipolare strutture simboliche ricorsive. La “narrow syntax” di Hauser et al. (2002) sembra puntare esattamente in questa direzione, ovvero verso l’esistenza di un nucleo autonomamente “linguistico” della cognizione che, pur interfacciandosi con i moduli cognitivi deputati all’organizzazione concettuale o all’elaborazione dell’informazione sensomotoria, ad essi non è comunque riducibile, poiché obbedisce a vincoli che le sono propri. Questi non sono interpretabili in senso puramente funzionalistico, in quanto sono virtualmente non spiegabili (ontogeneticamente e filogeneticamente) con le funzioni comunicative per le quali le strutture sono usate (Jackendoff e Pinker (2005) ad esempio criticano Hauser et al. (2002) proprio su questo punto, ovvero per il loro rifiuto di concepire il linguaggio come un prodotto dell’adattamento in funzione della comunicazione). Secondo l’accezione chomskiana di autonomia, i meccanismi stessi di apprendimento del linguaggio sono speciali e comunque non riducibili a principi generali di astrazione induttiva dal dato fattuale: la facoltà del linguaggio contiene invece elementi a priori che le sono propri e che guidano la maturazione delle strutture che essa si trova a governare nella competenza linguistica del parlante adulto.
Lenci, Alessandro
From context to meaning: Distributional models of the lexicon in linguistics and cognitive science, special issue of the Italian Journal of Linguistics Miscellaneous
2008.
@misc{ 11568_127044,
title = {From context to meaning: Distributional models of the lexicon in linguistics and cognitive science, special issue of the Italian Journal of Linguistics},
author = {Alessandro Lenci},
year = {2008},
date = {2008-01-01},
journal = {RIVISTA DI LINGUISTICA},
volume = {20},
publisher = {Pacini Editore},
address = {OSPEDALETTO},
abstract = {The aim of this thematic issue is to foster a critical debate on distributional approaches to meaning, by bringing together original contributions from leading computational linguists, lexical semanticists and psychologists.},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
The aim of this thematic issue is to foster a critical debate on distributional approaches to meaning, by bringing together original contributions from leading computational linguists, lexical semanticists and psychologists.
Lenci, Alessandro
Distributional semantics in linguistic and cognitive research Journal Article
In: RIVISTA DI LINGUISTICA, vol. 20, no. 1, pp. 1–30, 2008.
@article{ 11568_121673,
title = {Distributional semantics in linguistic and cognitive research},
author = {Alessandro Lenci},
year = {2008},
date = {2008-01-01},
journal = {RIVISTA DI LINGUISTICA},
volume = {20},
number = {1},
pages = {1–30},
abstract = {The hypothesis that word co-occurrence statistics extracted from text corpora can provide a basis for semantic representations has been gaining growing attention both in computational linguistics and in cognitive science. The terms distributional, context-theoretic, corpus- based or statistical can all be used (almost interchangeably) to qualify a rich family of approaches to semantics that share a “usage-based” perspective on meaning, and assume that the statistical distribution of words in context plays a key role in characterizing their semantic behavior. Besides this common core, many differences exist depend- ing on the specific mathematical and computational techniques, the type of semantic properties associated with text distributions, the definition of the linguistic context used to determine the combinato- rial spaces of lexical items, etc. Yet, at a closer look, we may discover that the commonalities are more than we could expect prima facie, and that a general model of meaning can indeed be discerned behind the differences, a model that formulates specific hypotheses on the format of semantic representations, and on the way they are built and processed by the human mind.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The hypothesis that word co-occurrence statistics extracted from text corpora can provide a basis for semantic representations has been gaining growing attention both in computational linguistics and in cognitive science. The terms distributional, context-theoretic, corpus- based or statistical can all be used (almost interchangeably) to qualify a rich family of approaches to semantics that share a “usage-based” perspective on meaning, and assume that the statistical distribution of words in context plays a key role in characterizing their semantic behavior. Besides this common core, many differences exist depend- ing on the specific mathematical and computational techniques, the type of semantic properties associated with text distributions, the definition of the linguistic context used to determine the combinato- rial spaces of lexical items, etc. Yet, at a closer look, we may discover that the commonalities are more than we could expect prima facie, and that a general model of meaning can indeed be discerned behind the differences, a model that formulates specific hypotheses on the format of semantic representations, and on the way they are built and processed by the human mind.
Dell'Orletta, F.; Lenci, Alessandro; Marchi, S.; Montemagni, S.; Pirrelli, V.; Venturi, G.
Dal testo alla conoscenza e ritorno: estrazione terminologica e annotazione semantica di basi documentali di dominio Journal Article
In: AIDA INFORMAZIONI, pp. 185–206, 2008.
@article{ 11568_125771,
title = {Dal testo alla conoscenza e ritorno: estrazione terminologica e annotazione semantica di basi documentali di dominio},
author = {F. Dell'Orletta and Alessandro Lenci and S. Marchi and S. Montemagni and V. Pirrelli and G. Venturi},
year = {2008},
date = {2008-01-01},
journal = {AIDA INFORMAZIONI},
pages = {185–206},
abstract = {The paper focuses on the automatic extracton of domain knowledge from Italian legal texts and presents a fully-implemented ontology learning system that includes a battery of tools for Natural Language Processing , statistical text analysis and machine learning},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The paper focuses on the automatic extracton of domain knowledge from Italian legal texts and presents a fully-implemented ontology learning system that includes a battery of tools for Natural Language Processing , statistical text analysis and machine learning
Lenci, Alessandro
Covariation can be (part of) meaning Journal Article
In: RIVISTA DI LINGUISTICA, vol. 20, no. 1, pp. 269–276, 2008.
@article{ 11568_118721,
title = {Covariation can be (part of) meaning},
author = {Alessandro Lenci},
year = {2008},
date = {2008-01-01},
journal = {RIVISTA DI LINGUISTICA},
volume = {20},
number = {1},
pages = {269–276},
abstract = {Glenberg and Metha (henceforth GM) argue against the equivalence
between meaning and covariation constraints among words
that is assumed more or less strongly by (psycho)computational models
adopting the distributional hypothesis (DH). They support their
argument with a pair of experiments in which a group of subjects is
trained to learn the distributional (covariation) constraints of respectively
non-linguistic (unlabeled radio buttons) and linguistic (partially
labeled radio buttons) stimuli representing feature distribution patterns
of different types of two-wheel vehicles (scooters, motorcycles,
bikes, etc.).},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Glenberg and Metha (henceforth GM) argue against the equivalence
between meaning and covariation constraints among words
that is assumed more or less strongly by (psycho)computational models
adopting the distributional hypothesis (DH). They support their
argument with a pair of experiments in which a group of subjects is
trained to learn the distributional (covariation) constraints of respectively
non-linguistic (unlabeled radio buttons) and linguistic (partially
labeled radio buttons) stimuli representing feature distribution patterns
of different types of two-wheel vehicles (scooters, motorcycles,
bikes, etc.).
between meaning and covariation constraints among words
that is assumed more or less strongly by (psycho)computational models
adopting the distributional hypothesis (DH). They support their
argument with a pair of experiments in which a group of subjects is
trained to learn the distributional (covariation) constraints of respectively
non-linguistic (unlabeled radio buttons) and linguistic (partially
labeled radio buttons) stimuli representing feature distribution patterns
of different types of two-wheel vehicles (scooters, motorcycles,
bikes, etc.).
Baroni, M.; Lenci, Alessandro
Concepts and properties in word spaces Journal Article
In: RIVISTA DI LINGUISTICA, vol. 20, no. 1, pp. 55–88, 2008.
@article{ 11568_118722,
title = {Concepts and properties in word spaces},
author = {M. Baroni and Alessandro Lenci},
year = {2008},
date = {2008-01-01},
journal = {RIVISTA DI LINGUISTICA},
volume = {20},
number = {1},
pages = {55–88},
abstract = {Properties play a central role in most theories of conceptual
knowledge. Since computational models derived from word co-occurrence statistics have been claimed to provide a natural basis for semantic representations, the question arises of whether such models are capable of producing reasonable property-based descriptions of concepts, and whether these descriptions are similar to those elicited from humans. This article presents a qualitative analysis of the properties generated by humans in two different settings, as well as those
produced, for the same concepts, by two computational models. In order to find high-level generalizations, the analysis is conducted in terms of property types, i.e., categorizing properties into classes such as functional and taxonomic properties. We discover that differences and similarities among models cut across the human/computational distinction, suggesting on the one hand caution in making broad generalizations, e.g., about “grounded” and “amodal” approaches, and, on the other, that different models might reveal different facets of meaning, and thus they should rather be integrated than seen as rival ways to get at the same information.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Properties play a central role in most theories of conceptual
knowledge. Since computational models derived from word co-occurrence statistics have been claimed to provide a natural basis for semantic representations, the question arises of whether such models are capable of producing reasonable property-based descriptions of concepts, and whether these descriptions are similar to those elicited from humans. This article presents a qualitative analysis of the properties generated by humans in two different settings, as well as those
produced, for the same concepts, by two computational models. In order to find high-level generalizations, the analysis is conducted in terms of property types, i.e., categorizing properties into classes such as functional and taxonomic properties. We discover that differences and similarities among models cut across the human/computational distinction, suggesting on the one hand caution in making broad generalizations, e.g., about “grounded” and “amodal” approaches, and, on the other, that different models might reveal different facets of meaning, and thus they should rather be integrated than seen as rival ways to get at the same information.
knowledge. Since computational models derived from word co-occurrence statistics have been claimed to provide a natural basis for semantic representations, the question arises of whether such models are capable of producing reasonable property-based descriptions of concepts, and whether these descriptions are similar to those elicited from humans. This article presents a qualitative analysis of the properties generated by humans in two different settings, as well as those
produced, for the same concepts, by two computational models. In order to find high-level generalizations, the analysis is conducted in terms of property types, i.e., categorizing properties into classes such as functional and taxonomic properties. We discover that differences and similarities among models cut across the human/computational distinction, suggesting on the one hand caution in making broad generalizations, e.g., about “grounded” and “amodal” approaches, and, on the other, that different models might reveal different facets of meaning, and thus they should rather be integrated than seen as rival ways to get at the same information.
Zarcone, A.; Lenci, Alessandro
Computational Models of Event Type Classification in Context Conference
Proceedings of LREC 2008, 2008, ISBN: 2951740840.
@conference{ 11568_121457,
title = {Computational Models of Event Type Classification in Context},
author = {A. Zarcone and Alessandro Lenci},
url = {http://www.lrec-conf.org/proceedings/lrec2008/pdf/315_paper.pdf},
isbn = {2951740840},
year = {2008},
date = {2008-01-01},
booktitle = {Proceedings of LREC 2008},
pages = {1232–1238},
abstract = {Verb lexical semantic properties are only one of the factors that contribute to the determination of the event type expressed by a sentence, which is instead the result of a complex interplay between the verb meaning and its linguistic context. We report on two computational models for the automatic identification of event type in Italian. Both models use linguistically-motivated features extracted from Italian corpora. The main goal of our experiments is to evaluate the contribution of different types of linguistic indicators to identify the event type of a sentence, as well as to model various cases of context-driven event type shift. In the first model, event type identification has been modelled as a supervised classification task, performed with Maximum Entropy classifiers. In the second model, Self-Organizing Maps have been used to define and identify event types in an unsupervised way. The interaction of various contextual factors in determining the event type expressed by a sentence makes event type identification a highly challenging task. Computational models can help us to shed new light on the real structure of event type classes as well as to gain a better understanding of context-driven semantic shifts.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Verb lexical semantic properties are only one of the factors that contribute to the determination of the event type expressed by a sentence, which is instead the result of a complex interplay between the verb meaning and its linguistic context. We report on two computational models for the automatic identification of event type in Italian. Both models use linguistically-motivated features extracted from Italian corpora. The main goal of our experiments is to evaluate the contribution of different types of linguistic indicators to identify the event type of a sentence, as well as to model various cases of context-driven event type shift. In the first model, event type identification has been modelled as a supervised classification task, performed with Maximum Entropy classifiers. In the second model, Self-Organizing Maps have been used to define and identify event types in an unsupervised way. The interaction of various contextual factors in determining the event type expressed by a sentence makes event type identification a highly challenging task. Computational models can help us to shed new light on the real structure of event type classes as well as to gain a better understanding of context-driven semantic shifts.
Lenci, Alessandro; Dell'Orletta, F.
Combinazioni di parole e spazi semantici: un'analisi computazionale dei testi di Giordano Bruno Book Chapter
In: Seminari SIGNUM 2005, pp. 143–161, Scuola Normale Superiore, Pisa, 2008, ISBN: 9788876423185.
@inbook{ 11568_119365,
title = {Combinazioni di parole e spazi semantici: un'analisi computazionale dei testi di Giordano Bruno},
author = {Alessandro Lenci and F. Dell'Orletta},
isbn = {9788876423185},
year = {2008},
date = {2008-01-01},
booktitle = {Seminari SIGNUM 2005},
pages = {143–161},
publisher = {Scuola Normale Superiore},
address = {Pisa},
abstract = {L’obiettivo di questo lavoro è mostrare come nuove e interessanti prospettive di indagine possano venire dall’applicazione all’analisi dei testi filosofici di metodi avanzati di linguistica computazionale e di rappresentazione del significato basati sulla costruzione automatica di spazi di similarità semantica determinati dalle modalità con cui le parole si distribuiscono e si combinano in un testo. A tale scopo, verranno illustrati i risultati di alcuni esperimenti condotti sugli Eroici Furori (1585) di Giordano Bruno, mostrando come le tecniche di semantica computazionale permettano di cogliere aspetti interessanti delle dinamiche del senso che si realizzano nel testo e che possono costituire tracce utili all’esplorazione del pensiero bruniano.},
keywords = {},
pubstate = {published},
tppubtype = {inbook}
}
L’obiettivo di questo lavoro è mostrare come nuove e interessanti prospettive di indagine possano venire dall’applicazione all’analisi dei testi filosofici di metodi avanzati di linguistica computazionale e di rappresentazione del significato basati sulla costruzione automatica di spazi di similarità semantica determinati dalle modalità con cui le parole si distribuiscono e si combinano in un testo. A tale scopo, verranno illustrati i risultati di alcuni esperimenti condotti sugli Eroici Furori (1585) di Giordano Bruno, mostrando come le tecniche di semantica computazionale permettano di cogliere aspetti interessanti delle dinamiche del senso che si realizzano nel testo e che possono costituire tracce utili all’esplorazione del pensiero bruniano.
2007
Jezek, E.; Lenci, Alessandro
When GL meets the corpus: a data-driven investigation of semantic types and coercion phenomena Conference
Fourth International Workshop on Generative Approaches to the Lexicon, 2007.
@conference{ 11568_115299,
title = {When GL meets the corpus: a data-driven investigation of semantic types and coercion phenomena},
author = {E. Jezek and Alessandro Lenci},
year = {2007},
date = {2007-01-01},
booktitle = {Fourth International Workshop on Generative Approaches to the Lexicon},
pages = {44–52},
abstract = {In this paper we present an analysis of corpusderived V-Object combinations aiming to provide a data-driven characterization of Semantic Types (STs) and improve our
understanding of how types behave compositionally, i.e. how they enter compositional processes and are modulated by
them. As a theoretical framework, we adopt the enriched compositional rules and the type system as presented in Pustejovsky (2007). Our main concerns are twofold: i.) first of all, we will show with a specific case-study how a data-driven investigation can shed light on the organization of the type system and onsemantic compositional operations affecting
types; ii.) starting from the results of this investigation, we intend to propose a general methodology for lexical modeling in which the Generative Lexicon (GL) theory and corpus analysis are deeply interwoven in a process of mutual feeding. In fact, we argue that, if on the one hand corpus data can help to anchor the study of lexical dynamics and type
system on empirical evidence, on the other hand GL can provide the crucial interpretative key for corpus data.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
In this paper we present an analysis of corpusderived V-Object combinations aiming to provide a data-driven characterization of Semantic Types (STs) and improve our
understanding of how types behave compositionally, i.e. how they enter compositional processes and are modulated by
them. As a theoretical framework, we adopt the enriched compositional rules and the type system as presented in Pustejovsky (2007). Our main concerns are twofold: i.) first of all, we will show with a specific case-study how a data-driven investigation can shed light on the organization of the type system and onsemantic compositional operations affecting
types; ii.) starting from the results of this investigation, we intend to propose a general methodology for lexical modeling in which the Generative Lexicon (GL) theory and corpus analysis are deeply interwoven in a process of mutual feeding. In fact, we argue that, if on the one hand corpus data can help to anchor the study of lexical dynamics and type
system on empirical evidence, on the other hand GL can provide the crucial interpretative key for corpus data.
understanding of how types behave compositionally, i.e. how they enter compositional processes and are modulated by
them. As a theoretical framework, we adopt the enriched compositional rules and the type system as presented in Pustejovsky (2007). Our main concerns are twofold: i.) first of all, we will show with a specific case-study how a data-driven investigation can shed light on the organization of the type system and onsemantic compositional operations affecting
types; ii.) starting from the results of this investigation, we intend to propose a general methodology for lexical modeling in which the Generative Lexicon (GL) theory and corpus analysis are deeply interwoven in a process of mutual feeding. In fact, we argue that, if on the one hand corpus data can help to anchor the study of lexical dynamics and type
system on empirical evidence, on the other hand GL can provide the crucial interpretative key for corpus data.
Guida, A.; Lenci, Alessandro
Semantic Properties of Word Associations to Italian Verbs Journal Article
In: RIVISTA DI LINGUISTICA, vol. 19, no. 2, pp. 293–326, 2007.
@article{ 11568_117449,
title = {Semantic Properties of Word Associations to Italian Verbs},
author = {A. Guida and Alessandro Lenci},
year = {2007},
date = {2007-01-01},
journal = {RIVISTA DI LINGUISTICA},
volume = {19},
number = {2},
pages = {293–326},
abstract = {This work is concerned with an investigation of verb associations, i.e., the words spontaneously called to mind in response to a given stimulus verb. We performed an elicitation task where native speakers were asked to spontaneously
list semantic associations for a list of Italian verbs. Starting from the assumption that the associations reflect highly salient linguistic and conceptual features of the verbs, the investigation is directed toward specifying the structural and conceptual types of associations by distinguishing and quantifying the relationships between stimuli and responses.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This work is concerned with an investigation of verb associations, i.e., the words spontaneously called to mind in response to a given stimulus verb. We performed an elicitation task where native speakers were asked to spontaneously
list semantic associations for a list of Italian verbs. Starting from the assumption that the associations reflect highly salient linguistic and conceptual features of the verbs, the investigation is directed toward specifying the structural and conceptual types of associations by distinguishing and quantifying the relationships between stimuli and responses.
list semantic associations for a list of Italian verbs. Starting from the assumption that the associations reflect highly salient linguistic and conceptual features of the verbs, the investigation is directed toward specifying the structural and conceptual types of associations by distinguishing and quantifying the relationships between stimuli and responses.
Bertuccelli, Marcella; Lenci, Alessandro
Lexical Complexity and the Texture of Meaning Conference
Lexical Complexity: Theoretical assemment and Translational Perspectives, Edizioni Plus srl, PISA, 2007, ISBN: 9788884924315.
@conference{ 11568_115772,
title = {Lexical Complexity and the Texture of Meaning},
author = {Marcella Bertuccelli and Alessandro Lenci},
isbn = {9788884924315},
year = {2007},
date = {2007-01-01},
booktitle = {Lexical Complexity: Theoretical assemment and Translational Perspectives},
pages = {15–33},
publisher = {Edizioni Plus srl},
address = {PISA},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Dell'Orletta, F.; Federico, M.; Lenci, Alessandro; Montemagni, S.; Pirrelli, V.
La massima Entropia per il part of speech tagging dell'italiano Journal Article
In: INTELLIGENZA ARTIFICIALE, vol. 4, pp. 10–11, 2007.
@article{ 11568_117081,
title = {La massima Entropia per il part of speech tagging dell'italiano},
author = {F. Dell'Orletta and M. Federico and Alessandro Lenci and S. Montemagni and V. Pirrelli},
url = {http://www.evalita.it/sites/evalita.fbk.eu/files/proceedings2007/03-IA-IV-2-ILCcnrUniPi-pos.pdf},
year = {2007},
date = {2007-01-01},
journal = {INTELLIGENZA ARTIFICIALE},
volume = {4},
pages = {10–11},
abstract = {L’articolo illustra le prestazioni del ILC-UniPi MaxEntPoS Tagger in Evalita 2007.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
L’articolo illustra le prestazioni del ILC-UniPi MaxEntPoS Tagger in Evalita 2007.
Baroni, M.; Lenci, Alessandro; Onnis, L.
ACL 2007 Workshop on Cognitive Aspects of Computational Language Acquisition, 2007.
@conference{ 11568_112529,
title = {ISA meets Lara: An incremental word space model for cognitively plausible simulations of semantic learning},
author = {M. Baroni and Alessandro Lenci and L. Onnis},
url = {http://aclweb.org/anthology-new/W/W07/W07-0607.pdf},
year = {2007},
date = {2007-01-01},
booktitle = {ACL 2007 Workshop on Cognitive Aspects of Computational Language Acquisition},
pages = {49–56},
abstract = {We introduce Incremental Semantic Analysis,
a fully incremental word space model
and we test it on longitudinal child-directed
speech data. On this task, our model outperforms
the related Random Indexing algorithm, as well as a SVD-based technique.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
We introduce Incremental Semantic Analysis,
a fully incremental word space model
and we test it on longitudinal child-directed
speech data. On this task, our model outperforms
the related Random Indexing algorithm, as well as a SVD-based technique.
a fully incremental word space model
and we test it on longitudinal child-directed
speech data. On this task, our model outperforms
the related Random Indexing algorithm, as well as a SVD-based technique.
Dell'Orletta, F.; Lenci, Alessandro; Montemagni, S.; Pirrelli, V.
Corpus-based Modelling of Grammar Variation Book Chapter
In: Language Resources and Linguistic Theories, pp. 38–55, FrancoAngeli, MILANO, 2007, ISBN: 9788846489449.
@inbook{ 11568_110041,
title = {Corpus-based Modelling of Grammar Variation},
author = {F. Dell'Orletta and Alessandro Lenci and S. Montemagni and V. Pirrelli},
isbn = {9788846489449},
year = {2007},
date = {2007-01-01},
booktitle = {Language Resources and Linguistic Theories},
pages = {38–55},
publisher = {FrancoAngeli},
address = {MILANO},
abstract = {Current research in natural language learning and processing supports the view that grammatical competence consists in mastering and integrating multiple, parallel “constraints” (Seidenberg and MacDonald 1999, MacWhinney 2004, Burzio 2005). During language comprehension, constraints are defined as a set of cues through which a speaker can successfully map a complex linguistic unit (a word form, a phrase, an utterance etc.) to its intended function in discourse. For example, in the Italian sentence arriva il treno (‘the train is approaching’), the noun phrase il treno is understood to play the role of subject due to an integrated cluster of cues concerning the position of the subject relative to the verb, noun-verb agreement, compliance of predicate selectional restrictions and general knowledge about the world. Conversely, in language production, constraints consist in discourse functions that are jointly mapped onto linguistic forms. If we want to translate arriva il treno into English, we have to be aware of the peculiar functional constraint positioning the subject before the verb in the target language.},
keywords = {},
pubstate = {published},
tppubtype = {inbook}
}
Current research in natural language learning and processing supports the view that grammatical competence consists in mastering and integrating multiple, parallel “constraints” (Seidenberg and MacDonald 1999, MacWhinney 2004, Burzio 2005). During language comprehension, constraints are defined as a set of cues through which a speaker can successfully map a complex linguistic unit (a word form, a phrase, an utterance etc.) to its intended function in discourse. For example, in the Italian sentence arriva il treno (‘the train is approaching’), the noun phrase il treno is understood to play the role of subject due to an integrated cluster of cues concerning the position of the subject relative to the verb, noun-verb agreement, compliance of predicate selectional restrictions and general knowledge about the world. Conversely, in language production, constraints consist in discourse functions that are jointly mapped onto linguistic forms. If we want to translate arriva il treno into English, we have to be aware of the peculiar functional constraint positioning the subject before the verb in the target language.
2006
Lenci, Alessandro
The Lexicon and the Boundaries of Compositionality Book Chapter
In: Truth and Games. Essays in Honor of Gabriel Sandu, pp. 119–138, Helsinki University Press, Helsinki, 2006, ISBN: 9519264574.
@inbook{ 11568_102385,
title = {The Lexicon and the Boundaries of Compositionality},
author = {Alessandro Lenci},
isbn = {9519264574},
year = {2006},
date = {2006-01-01},
booktitle = {Truth and Games. Essays in Honor of Gabriel Sandu},
pages = {119–138},
publisher = {Helsinki University Press},
address = {Helsinki},
abstract = {Sentence-level creativity and word-level semantic creativity can actually be reconciled once
we adopt a more sophisticated model of the lexicon. This type of solution is strongly
pursued within the GL theory, in which enriching lexical representations with theory-
constrained aspects of contextual knowledge is assumed to be the essential condition to
turn compositional processes into real generative devices of meaning multiplicity. Although
the idea of overcoming context-free lexical representations is surely a step forward with
respect to more conservative views of word meaning, its actual implementation in GL still
leaves many open issues. Representational devices like the qualia structure are important proposals for a more sophisticated architecture of the lexicon, but they need to be further
explored and constrained before being able to reach a fully satisfactory explanatory power.
The same holds true of the battery of extended semantic operations that are needed in
GL to generate sense creativity in contexts.
Promising theoretical prospectives are o®ered by distributional models of lexical representations. Notwistanding the many differences with GL, distributional models share
with it some core assumptions. In particular, they push to its extreme consequences the
idea itself of context-sensitive lexical representations. In distributional models, the re-
lationship between lexical items and their context of use is somehow inverted, with the latter directly entering into the constitution of the former. According to this approach, it is not only sense-extensions to be generated in contexts, but lexical representations
themselves, which emerge out of distribution of contexts of use. Assuming distributional semantic representations allows us to take into account the effect of polysemy in compositional processes, such as for instance the fact that polysemous items are associated with multiple similarity spaces whose shape and content can dramatically vary depending on the linguistic context of composition. Distributional models have become very popu-
lar nowadays especially for natural language processing, given the possibilities they offer to bootstrap semantic representations directly from corpus data. However, they are not without problems. Actually, Lenci et al. (2005) provide a critical discussion of various
types of of distributional models of meaning, which in many cases still have to prove their effective capacity to provide in-depth analyses of word meanings. Yet, notwithstanding
their limits, these models represent an important probe to explore lexical dynamics. In particular, distributional models seem to suggest that the possibility for language to tolerate compositional processes side by side to sense creation processes is rooted in the fact
that the boundaries between lexicon and context are much smoother and articulated than
is often assumed. Distributional model of the lexicon are able to simulate the dynamics
occurring between lexicon and context, and this way they can provide important insights
on the interplay between lexical variation and sentence creativity, allowing us to further
explore the boundaries of compositionality in natural language.},
keywords = {},
pubstate = {published},
tppubtype = {inbook}
}
Sentence-level creativity and word-level semantic creativity can actually be reconciled once
we adopt a more sophisticated model of the lexicon. This type of solution is strongly
pursued within the GL theory, in which enriching lexical representations with theory-
constrained aspects of contextual knowledge is assumed to be the essential condition to
turn compositional processes into real generative devices of meaning multiplicity. Although
the idea of overcoming context-free lexical representations is surely a step forward with
respect to more conservative views of word meaning, its actual implementation in GL still
leaves many open issues. Representational devices like the qualia structure are important proposals for a more sophisticated architecture of the lexicon, but they need to be further
explored and constrained before being able to reach a fully satisfactory explanatory power.
The same holds true of the battery of extended semantic operations that are needed in
GL to generate sense creativity in contexts.
Promising theoretical prospectives are o®ered by distributional models of lexical representations. Notwistanding the many differences with GL, distributional models share
with it some core assumptions. In particular, they push to its extreme consequences the
idea itself of context-sensitive lexical representations. In distributional models, the re-
lationship between lexical items and their context of use is somehow inverted, with the latter directly entering into the constitution of the former. According to this approach, it is not only sense-extensions to be generated in contexts, but lexical representations
themselves, which emerge out of distribution of contexts of use. Assuming distributional semantic representations allows us to take into account the effect of polysemy in compositional processes, such as for instance the fact that polysemous items are associated with multiple similarity spaces whose shape and content can dramatically vary depending on the linguistic context of composition. Distributional models have become very popu-
lar nowadays especially for natural language processing, given the possibilities they offer to bootstrap semantic representations directly from corpus data. However, they are not without problems. Actually, Lenci et al. (2005) provide a critical discussion of various
types of of distributional models of meaning, which in many cases still have to prove their effective capacity to provide in-depth analyses of word meanings. Yet, notwithstanding
their limits, these models represent an important probe to explore lexical dynamics. In particular, distributional models seem to suggest that the possibility for language to tolerate compositional processes side by side to sense creation processes is rooted in the fact
that the boundaries between lexicon and context are much smoother and articulated than
is often assumed. Distributional model of the lexicon are able to simulate the dynamics
occurring between lexicon and context, and this way they can provide important insights
on the interplay between lexical variation and sentence creativity, allowing us to further
explore the boundaries of compositionality in natural language.
we adopt a more sophisticated model of the lexicon. This type of solution is strongly
pursued within the GL theory, in which enriching lexical representations with theory-
constrained aspects of contextual knowledge is assumed to be the essential condition to
turn compositional processes into real generative devices of meaning multiplicity. Although
the idea of overcoming context-free lexical representations is surely a step forward with
respect to more conservative views of word meaning, its actual implementation in GL still
leaves many open issues. Representational devices like the qualia structure are important proposals for a more sophisticated architecture of the lexicon, but they need to be further
explored and constrained before being able to reach a fully satisfactory explanatory power.
The same holds true of the battery of extended semantic operations that are needed in
GL to generate sense creativity in contexts.
Promising theoretical prospectives are o®ered by distributional models of lexical representations. Notwistanding the many differences with GL, distributional models share
with it some core assumptions. In particular, they push to its extreme consequences the
idea itself of context-sensitive lexical representations. In distributional models, the re-
lationship between lexical items and their context of use is somehow inverted, with the latter directly entering into the constitution of the former. According to this approach, it is not only sense-extensions to be generated in contexts, but lexical representations
themselves, which emerge out of distribution of contexts of use. Assuming distributional semantic representations allows us to take into account the effect of polysemy in compositional processes, such as for instance the fact that polysemous items are associated with multiple similarity spaces whose shape and content can dramatically vary depending on the linguistic context of composition. Distributional models have become very popu-
lar nowadays especially for natural language processing, given the possibilities they offer to bootstrap semantic representations directly from corpus data. However, they are not without problems. Actually, Lenci et al. (2005) provide a critical discussion of various
types of of distributional models of meaning, which in many cases still have to prove their effective capacity to provide in-depth analyses of word meanings. Yet, notwithstanding
their limits, these models represent an important probe to explore lexical dynamics. In particular, distributional models seem to suggest that the possibility for language to tolerate compositional processes side by side to sense creation processes is rooted in the fact
that the boundaries between lexicon and context are much smoother and articulated than
is often assumed. Distributional model of the lexicon are able to simulate the dynamics
occurring between lexicon and context, and this way they can provide important insights
on the interplay between lexical variation and sentence creativity, allowing us to further
explore the boundaries of compositionality in natural language.
Dell'Orletta, F.; Lenci, Alessandro; Montemagni, S.; Pirrelli, V.
Language Resources and Evaluation Conference 2006 (LREC 2006), 2006, ISBN: 2951740824.
@conference{ 11568_108386,
title = {Searching Treebanks for Functional Constraints: Crosslingual Experiments in Grammatical Relations Assignment},
author = {F. Dell'Orletta and Alessandro Lenci and S. Montemagni and V. Pirrelli},
url = {http://www.lrec-conf.org/proceedings/lrec2006/pdf/651_pdf.pdf},
isbn = {2951740824},
year = {2006},
date = {2006-01-01},
booktitle = {Language Resources and Evaluation Conference 2006 (LREC 2006)},
pages = {433–438},
abstract = {We report here on a detailed quantitative analysis of distributional language data of both Italian and Czech, highlighting the relative contribution of a number of distributed grammatical factors to sentence-based identification of subjects and direct objects. The work is based on a Maximum Entropy model of stochastic resolution of grammatical conflicting constraints, and is demonstrably capable of putting explanatory theoretical accounts to the challenging test of an extensive, usage-based empirical verification.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
We report here on a detailed quantitative analysis of distributional language data of both Italian and Czech, highlighting the relative contribution of a number of distributed grammatical factors to sentence-based identification of subjects and direct objects. The work is based on a Maximum Entropy model of stochastic resolution of grammatical conflicting constraints, and is demonstrably capable of putting explanatory theoretical accounts to the challenging test of an extensive, usage-based empirical verification.
Dell'Orletta, F.; Lenci, Alessandro; Montemagni, S.; Pirrelli, V.
Proceedings of the COLING/ACL Workshop on Frontiers in Linguistically Annotated Corpora, 2006, ISBN: 1932432787.
@conference{ 11568_108728,
title = {Probing the Space of Grammatical Variation: Induction of Cross-Lingual Grammatical Constraints from Treebanks},
author = {F. Dell'Orletta and Alessandro Lenci and S. Montemagni and V. Pirrelli},
url = {http://aclweb.org/anthology-new/W/W06/W06-0604.pdf},
isbn = {1932432787},
year = {2006},
date = {2006-01-01},
booktitle = {Proceedings of the COLING/ACL Workshop on Frontiers in Linguistically Annotated Corpora},
pages = {21–28},
abstract = {quantitative analysis of distributional
language data of both Italian and Czech,
highlighting the relative contribution of a
number of distributed grammatical
factors to sentence-based identification of
subjects and direct objects. The work
uses a Maximum Entropy model of
stochastic resolution of conflicting
grammatical constraints and is
demonstrably capable of putting
explanatory theoretical accounts to the
test of usage-based empirical verification.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
quantitative analysis of distributional
language data of both Italian and Czech,
highlighting the relative contribution of a
number of distributed grammatical
factors to sentence-based identification of
subjects and direct objects. The work
uses a Maximum Entropy model of
stochastic resolution of conflicting
grammatical constraints and is
demonstrably capable of putting
explanatory theoretical accounts to the
test of usage-based empirical verification.
language data of both Italian and Czech,
highlighting the relative contribution of a
number of distributed grammatical
factors to sentence-based identification of
subjects and direct objects. The work
uses a Maximum Entropy model of
stochastic resolution of conflicting
grammatical constraints and is
demonstrably capable of putting
explanatory theoretical accounts to the
test of usage-based empirical verification.
PIER, Marco BERTINETTO; Lenci, Alessandro; Noccetti, Sabrina; Agonigi, Maddalena
Metodi quantitativi nello studio dell'acquisizione delle strutture tempo-aspettuali Journal Article
In: QUADERNI DEL LABORATORIO DI LINGUISTICA, vol. 6, 2006.
@article{ 11568_106745,
title = {Metodi quantitativi nello studio dell'acquisizione delle strutture tempo-aspettuali},
author = {Marco BERTINETTO PIER and Alessandro Lenci and Sabrina Noccetti and Maddalena Agonigi},
year = {2006},
date = {2006-01-01},
journal = {QUADERNI DEL LABORATORIO DI LINGUISTICA},
volume = {6},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Bartolini, R; Caracciolo, C; Giovannetti, E; Lenci, Alessandro; Marchi, S; Pirrelli, V; Spinsanti, L; Renso, C.
Creation and Use of Lexicons and Ontologies for Natural Language Interface to Databases Conference
Language Resources and Evaluation Conference 2006 (LREC 2006), 2006, ISBN: 2951740824.
@conference{ 11568_104253,
title = {Creation and Use of Lexicons and Ontologies for Natural Language Interface to Databases},
author = {R Bartolini and C Caracciolo and E Giovannetti and Alessandro Lenci and S Marchi and V Pirrelli and L Spinsanti and C. Renso},
url = {http://www.lrec-conf.org/proceedings/lrec2006/pdf/674_pdf.pdf},
isbn = {2951740824},
year = {2006},
date = {2006-01-01},
booktitle = {Language Resources and Evaluation Conference 2006 (LREC 2006)},
pages = {219–224},
abstract = {In this paper we present an original approach to natural language query interpretation which has been implemented within the FuLL (Fuzzy Logic and Language) Italian project of BC S.r.l. In particular, we discuss here the creation of linguistic and ontological resources, together with the exploitation of existing ones, for natural language-driven database access and retrieval. Both the database and the queries we experiment with are Italian, but the methodology we broach naturally extends to other languages.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
In this paper we present an original approach to natural language query interpretation which has been implemented within the FuLL (Fuzzy Logic and Language) Italian project of BC S.r.l. In particular, we discuss here the creation of linguistic and ontological resources, together with the exploitation of existing ones, for natural language-driven database access and retrieval. Both the database and the queries we experiment with are Italian, but the methodology we broach naturally extends to other languages.
Bassi, Simonetta; Dell'Orletta, F.; Esposito, D.; Lenci, Alessandro
Computational linguistics meets philosophy: a Latent Semantic Analysis of Giordano Bruno's texts Conference
Proceedings of the LREC 2006 Workshop Towards Computational Models of Literary Analysis, 2006.
@conference{ 11568_100787,
title = {Computational linguistics meets philosophy: a Latent Semantic Analysis of Giordano Bruno's texts},
author = {Simonetta Bassi and F. Dell'Orletta and D. Esposito and Alessandro Lenci},
year = {2006},
date = {2006-01-01},
booktitle = {Proceedings of the LREC 2006 Workshop Towards Computational Models of Literary Analysis},
pages = {8–15},
abstract = {Traditional methods such as concordance lists are not able to provide us with a real access to the semantic space of a philosophical text
and to its dynamics. In this paper, we will argue that new insights on these points can come from the application of more sophisticated
mathematical and computational methods of meaning representation, based on the automatic construction of text-driven word
similarity spaces out of the way word distribute and co-occur in texts. More specifically, we report on a current research in which
semantic spaces are dynamically built by applying a variation of Latent Semantic Analysis to the Eroici furori by Giordano Bruno, the
XVI century Italian philosopher.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Traditional methods such as concordance lists are not able to provide us with a real access to the semantic space of a philosophical text
and to its dynamics. In this paper, we will argue that new insights on these points can come from the application of more sophisticated
mathematical and computational methods of meaning representation, based on the automatic construction of text-driven word
similarity spaces out of the way word distribute and co-occur in texts. More specifically, we report on a current research in which
semantic spaces are dynamically built by applying a variation of Latent Semantic Analysis to the Eroici furori by Giordano Bruno, the
XVI century Italian philosopher.
and to its dynamics. In this paper, we will argue that new insights on these points can come from the application of more sophisticated
mathematical and computational methods of meaning representation, based on the automatic construction of text-driven word
similarity spaces out of the way word distribute and co-occur in texts. More specifically, we report on a current research in which
semantic spaces are dynamically built by applying a variation of Latent Semantic Analysis to the Eroici furori by Giordano Bruno, the
XVI century Italian philosopher.
Bassi, Simonetta; Dell'Orletta, F.; Esposito, D.; Lenci, Alessandro
Computational Linguistics Meets Philosophy: A Latent Semantic Analysis of Giordano Bruno's Texts Journal Article
In: RINASCIMENTO, vol. 46, pp. 631–647, 2006.
@article{ 11568_104630,
title = {Computational Linguistics Meets Philosophy: A Latent Semantic Analysis of Giordano Bruno's Texts},
author = {Simonetta Bassi and F. Dell'Orletta and D. Esposito and Alessandro Lenci},
year = {2006},
date = {2006-01-01},
journal = {RINASCIMENTO},
volume = {46},
pages = {631–647},
abstract = {Traditional methods such as concordance lists are not able to provide us with a real access to the semantic space of a philosophical text
and to its dynamics. In this paper, we will argue that new insights on these points can come from the application of more sophisticated
mathematical and computational methods of meaning representation, based on the automatic construction of text-driven word
similarity spaces out of the way word distribute and co-occur in texts. More specifically, we report on a current research in which
semantic spaces are dynamically built by applying a variation of Latent Semantic Analysis to the Eroici furori by Giordano Bruno, the
XVI century Italian philosopher.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Traditional methods such as concordance lists are not able to provide us with a real access to the semantic space of a philosophical text
and to its dynamics. In this paper, we will argue that new insights on these points can come from the application of more sophisticated
mathematical and computational methods of meaning representation, based on the automatic construction of text-driven word
similarity spaces out of the way word distribute and co-occur in texts. More specifically, we report on a current research in which
semantic spaces are dynamically built by applying a variation of Latent Semantic Analysis to the Eroici furori by Giordano Bruno, the
XVI century Italian philosopher.
and to its dynamics. In this paper, we will argue that new insights on these points can come from the application of more sophisticated
mathematical and computational methods of meaning representation, based on the automatic construction of text-driven word
similarity spaces out of the way word distribute and co-occur in texts. More specifically, we report on a current research in which
semantic spaces are dynamically built by applying a variation of Latent Semantic Analysis to the Eroici furori by Giordano Bruno, the
XVI century Italian philosopher.
Lenci, Alessandro; Simonetta, M.; Vito, P.
Acquisition and Representation of Word Meaning. Theoretical and Computational Perspectives Book
Istituti Editoriali e Poligrafici Internazionali, GHEZZANO (PI), 2006, ISBN: 9788881474134.
@book{<LineBreak> 11568_104112,
title = {Acquisition and Representation of Word Meaning. Theoretical and Computational Perspectives},
author = {Alessandro Lenci and M. Simonetta and P. Vito},
isbn = {9788881474134},
year = {2006},
date = {2006-01-01},
urldate = {2006-01-01},
publisher = {Istituti Editoriali e Poligrafici Internazionali},
address = {GHEZZANO (PI)},
abstract = {La quantità di conoscenza necessaria per far luce sui significati di parole legate reciprocamente in un contesto o distribuite in classi lessico-semantiche sembra eccedere i limiti della consapevolezza umana e della possibilità descrittiva. Particolarmente a questo livello di analisi linguistica sembra allora esserci necessità di metodi automatici per filtrare, strutturare e classificare l'evidenza semantica attraverso lo studio di un gran numero di usi della parola in un contesto. Il volume intende porre l'attenzione sull'interazione fra le tecniche per trarre informazioni semantiche da un corpus di dati e i metodi formali di rappresentazione della conoscenza linguistica.},
keywords = {},
pubstate = {published},
tppubtype = {book}
}
La quantità di conoscenza necessaria per far luce sui significati di parole legate reciprocamente in un contesto o distribuite in classi lessico-semantiche sembra eccedere i limiti della consapevolezza umana e della possibilità descrittiva. Particolarmente a questo livello di analisi linguistica sembra allora esserci necessità di metodi automatici per filtrare, strutturare e classificare l'evidenza semantica attraverso lo studio di un gran numero di usi della parola in un contesto. Il volume intende porre l'attenzione sull'interazione fra le tecniche per trarre informazioni semantiche da un corpus di dati e i metodi formali di rappresentazione della conoscenza linguistica.
Lenci, Alessandro; Montemagni, S.; Pirrelli, V.
Acquiring and Representing Meaning. Theoretical and Computational Perspectives Book Chapter
In: Acquisition and Representation of Word Meaning. Theoretical and Computational Perspectives, pp. 19–66, Istituti Editoriali e Poligrafici Internazionali, GHEZZANO (PI), 2006, ISBN: 9788881474134.
@inbook{ 11568_108420,
title = {Acquiring and Representing Meaning. Theoretical and Computational Perspectives},
author = {Alessandro Lenci and S. Montemagni and V. Pirrelli},
isbn = {9788881474134},
year = {2006},
date = {2006-01-01},
booktitle = {Acquisition and Representation of Word Meaning. Theoretical and Computational Perspectives},
pages = {19–66},
publisher = {Istituti Editoriali e Poligrafici Internazionali},
address = {GHEZZANO (PI)},
abstract = {Modelling the way word meanings dynamically function and combine
in communicative contexts, evolve through learning and are categorised
through high-level semantic classes presents one of the most di±cult
challenges for cognitive science, and is a large stumbling block on the
way to developing advanced arti¯cial systems for full text understanding.
The problem of the form of semantic knowledge typically presents itself
as a representation issue: i.e. what is the aptest way of representing the
meaning of words and of the complex expressions they enter into? Pro-
viding satisfactory answers to these questions is an essential requirement
for explaining the e®ective use of semantic knowledge in concrete cog-
nitive abilities. This is extremely important also in an engineering and
computational perspective, as a key to a deeper understanding of the
constructive principles underpinning the design of intelligent artifacts
like robots and other arti¯cial intelligent agents. Similarly, the issue
of semantic dynamics has a crucial role in modelling human cognition,
since cognitive agents constantly update and revise their knowledge, ac-
quire new words, assign new meanings to already known words, etc},
keywords = {},
pubstate = {published},
tppubtype = {inbook}
}
Modelling the way word meanings dynamically function and combine
in communicative contexts, evolve through learning and are categorised
through high-level semantic classes presents one of the most di±cult
challenges for cognitive science, and is a large stumbling block on the
way to developing advanced arti¯cial systems for full text understanding.
The problem of the form of semantic knowledge typically presents itself
as a representation issue: i.e. what is the aptest way of representing the
meaning of words and of the complex expressions they enter into? Pro-
viding satisfactory answers to these questions is an essential requirement
for explaining the e®ective use of semantic knowledge in concrete cog-
nitive abilities. This is extremely important also in an engineering and
computational perspective, as a key to a deeper understanding of the
constructive principles underpinning the design of intelligent artifacts
like robots and other arti¯cial intelligent agents. Similarly, the issue
of semantic dynamics has a crucial role in modelling human cognition,
since cognitive agents constantly update and revise their knowledge, ac-
quire new words, assign new meanings to already known words, etc
in communicative contexts, evolve through learning and are categorised
through high-level semantic classes presents one of the most di±cult
challenges for cognitive science, and is a large stumbling block on the
way to developing advanced arti¯cial systems for full text understanding.
The problem of the form of semantic knowledge typically presents itself
as a representation issue: i.e. what is the aptest way of representing the
meaning of words and of the complex expressions they enter into? Pro-
viding satisfactory answers to these questions is an essential requirement
for explaining the e®ective use of semantic knowledge in concrete cog-
nitive abilities. This is extremely important also in an engineering and
computational perspective, as a key to a deeper understanding of the
constructive principles underpinning the design of intelligent artifacts
like robots and other arti¯cial intelligent agents. Similarly, the issue
of semantic dynamics has a crucial role in modelling human cognition,
since cognitive agents constantly update and revise their knowledge, ac-
quire new words, assign new meanings to already known words, etc
2005
Lenci, Alessandro; Montemagni, S.; Pirrelli, V.
Testo e computer. Introduzione alla linguistica computazionale Book
Carocci Editore, ROMA, 2005, ISBN: 9788843034253.
@book{ 11568_94724,
title = {Testo e computer. Introduzione alla linguistica computazionale},
author = {Alessandro Lenci and S. Montemagni and V. Pirrelli},
isbn = {9788843034253},
year = {2005},
date = {2005-01-01},
publisher = {Carocci Editore},
address = {ROMA},
abstract = {In che modo il computer può aiutarci a comprendere come funziona la nostra lingua? Cosa significa analizzare un testo con l'aiuto di un calcolatore? In che misura possiamo estendere le potenzialità del computer rendendolo capace di interagire con gli utenti umani nella loro lingua? Queste e altre domande sono l'oggetto di indagine della linguistica computazionale, una disciplina che ha al suo centro proprio il rapporto tra lingua e computer. Il libro fornisce gli elementi di base della linguistica computazionale partendo da un interesse primario per il testo, la sua struttura e il suo contenuto. Il volume propone una sintesi equilibrata e accessibile tra sapere e fare, nozioni di base e loro applicazione.},
keywords = {},
pubstate = {published},
tppubtype = {book}
}
In che modo il computer può aiutarci a comprendere come funziona la nostra lingua? Cosa significa analizzare un testo con l'aiuto di un calcolatore? In che misura possiamo estendere le potenzialità del computer rendendolo capace di interagire con gli utenti umani nella loro lingua? Queste e altre domande sono l'oggetto di indagine della linguistica computazionale, una disciplina che ha al suo centro proprio il rapporto tra lingua e computer. Il libro fornisce gli elementi di base della linguistica computazionale partendo da un interesse primario per il testo, la sua struttura e il suo contenuto. Il volume propone una sintesi equilibrata e accessibile tra sapere e fare, nozioni di base e loro applicazione.
Lenci, Alessandro
La sintassi tra ottimalità e probabilità. Soggetti e oggetti in una grammatica stocastica dell’italiano Journal Article
In: STUDI E SAGGI LINGUISTICI, vol. 42, pp. 43–87, 2005.
@article{ 11568_99544.1,
title = {La sintassi tra ottimalità e probabilità. Soggetti e oggetti in una grammatica stocastica dell’italiano},
author = {Alessandro Lenci},
year = {2005},
date = {2005-01-01},
journal = {STUDI E SAGGI LINGUISTICI},
volume = {42},
pages = {43–87},
abstract = {Le grammatiche OT stocastiche simulate con OTSoft riproducono proprietà rilevanti nella distribuzione di S e O in italiano. In particolare, il ruolo dell’animatezza e della definitezza nella distribuzione delle relazioni grammaticali viene formalmente rappresentato come l’effetto di gerarchie universali di marcatezza che agiscono in questa lingua secondo modalità probabilistiche. Ciò consente di analizzare la distribuzione di S e O in italiano nell’ambito di una spiegazione generale del ruolo delle categorie di animatezza e di definitezza nella sintassi delle lingue naturali.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Le grammatiche OT stocastiche simulate con OTSoft riproducono proprietà rilevanti nella distribuzione di S e O in italiano. In particolare, il ruolo dell’animatezza e della definitezza nella distribuzione delle relazioni grammaticali viene formalmente rappresentato come l’effetto di gerarchie universali di marcatezza che agiscono in questa lingua secondo modalità probabilistiche. Ciò consente di analizzare la distribuzione di S e O in italiano nell’ambito di una spiegazione generale del ruolo delle categorie di animatezza e di definitezza nella sintassi delle lingue naturali.
Dell'Orletta, F.; Lenci, Alessandro; Montemagni, S.; Pirrelli, V.
Climbing the Path to Grammar: a Maximum Entropy Model of Subject/Object Learning Conference
Proceedings of the Workshop on Psychocomputational Models of Human Language Acquisition, 2005.
@conference{ 11568_95717,
title = {Climbing the Path to Grammar: a Maximum Entropy Model of Subject/Object Learning},
author = {F. Dell'Orletta and Alessandro Lenci and S. Montemagni and V. Pirrelli},
year = {2005},
date = {2005-01-01},
booktitle = {Proceedings of the Workshop on Psychocomputational Models of Human Language Acquisition},
pages = {72–81},
abstract = {In this paper, we discuss an applic ation of
Maximum Entropy to modeling the acquisition
of subject and object processing in
Italian. The model is able to learn from
corpus data a set of experimentally and
theoretically well-motivated linguistic
constraints, as well as their relative salience
in Italian grammar development and
processing. The model is also shown to
acquire robust syntactic generalizations
by relying on the evidence provided by a
small number of high token frequency
verbs only. These results are consistent
with current research focusing on the role
of high frequency verbs in allowing children
to converge on the most salient constraints
in the grammar.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
In this paper, we discuss an applic ation of
Maximum Entropy to modeling the acquisition
of subject and object processing in
Italian. The model is able to learn from
corpus data a set of experimentally and
theoretically well-motivated linguistic
constraints, as well as their relative salience
in Italian grammar development and
processing. The model is also shown to
acquire robust syntactic generalizations
by relying on the evidence provided by a
small number of high token frequency
verbs only. These results are consistent
with current research focusing on the role
of high frequency verbs in allowing children
to converge on the most salient constraints
in the grammar.
Maximum Entropy to modeling the acquisition
of subject and object processing in
Italian. The model is able to learn from
corpus data a set of experimentally and
theoretically well-motivated linguistic
constraints, as well as their relative salience
in Italian grammar development and
processing. The model is also shown to
acquire robust syntactic generalizations
by relying on the evidence provided by a
small number of high token frequency
verbs only. These results are consistent
with current research focusing on the role
of high frequency verbs in allowing children
to converge on the most salient constraints
in the grammar.