Carving verb classes from corpora

In this paper, I discuss some methodological problems arising from the use of corpus data for semantic verb classification. In particular, I present a computational framework to describe the distributional properties of Italian verbs using linguistic data automatically extracted from a large corpus. This information is used to build a distribution-based classification of a set of Italian verbs. It is small scale notwithstanding, this case study will provide evidence for the complex interplay between syntactic and semantic verb features.

[1]  Christopher R. Johnson,et al.  Background to Framenet , 2003 .

[2]  James Pustejovsky,et al.  The Generative Lexicon , 1995, CL.

[3]  Paola Merlo,et al.  The Notion of Argument in Prepositional Phrase Attachment , 2006, Computational Linguistics.

[4]  Barbara B. Levin,et al.  English verb classes and alternations , 1993 .

[5]  Guy Aston,et al.  Introducing the La Repubblica Corpus: A Large, Annotated, TEI(XML)-compliant Corpus of Newspaper Italian , 2004, LREC.

[6]  Suzanne Stevenson,et al.  Automatic Verb Classification Based on Statistical Distributions of Argument Structure , 2001, CL.

[7]  Mirella Lapata,et al.  Verb Class Disambiguation Using Informative Priors , 2004, CL.

[8]  Patrick Hanks,et al.  Contextual dependency and lexical sets , 1996 .

[9]  Neville Ryant,et al.  A large-scale classification of English verbs , 2008, Lang. Resour. Evaluation.

[10]  Alessandro Lenci,et al.  Distributional semantics in linguistic and cognitive research , 2008 .

[11]  김두식,et al.  English Verb Classes and Alternations , 2006 .

[12]  Anna Korhonen,et al.  Automatic Lexical Classification – Balancing between Machine Learning and Linguistics , 2009, PACLIC.

[13]  Fredric C. Gey,et al.  Proceedings of LREC , 2010 .

[14]  James Pustejovsky,et al.  A Pattern Dictionary for Natural Language Processing , 2005 .

[15]  Chris Brew,et al.  Which Are the Best Features for Automatic Verb Classification , 2008, ACL.

[16]  Marc Light,et al.  Statistical models for the induction and use of selectional preferences , 2002, Cogn. Sci..

[17]  Anna Korhonen,et al.  Improving Verb Clustering with Automatically Acquired Selectional Preferences , 2009, EMNLP.

[18]  Stefan Evert,et al.  Corpora and collocations , 2007 .

[19]  Sabine Schulte im Walde.  44. The induction of verb frames and verb classes from corpora , 2009 .

[20]  Zellig S. Harris,et al.  Distributional Structure , 1954 .

[21]  Martha Palmer,et al.  Verbnet: a broad-coverage, comprehensive verb lexicon , 2005 .

[22]  Suzanne Stevenson,et al.  A General Feature Space for Automatic Verb Classification , 2003, EACL.

[23]  Antonietta Alonge,et al.  ItalWordNet: a Large Semantic Database for Italian , 2000, LREC.

[24]  Felice Dell'Orletta,et al.  Reverse Revision and Linear Tree Combination for Dependency Parsing , 2009, HLT-NAACL.

[25]  Lenhart K. Schubert.  Semantic Representation , 2015, AAAI.

[26]  Katrin Erk,et al.  A Simple, Similarity-based Model for Selectional Preferences , 2007, ACL.

[27]  Beth Levin,et al.  English Verb Classes and Alternations: A Preliminary Investigation , 1993 .

[28]  Nicoletta Calzolari,et al.  SIMPLE: A General Framework for the Development of Multilingual Lexicons , 2000, LREC.

[29]  Diana McCarthy,et al.  Lexical acquisition at the syntax-semantics interface : diathesis alternations, subcategorization frames and selectional preferences , 2001 .

[30]  Katrin Erk,et al.  Comparing and combining semantic verb classifications , 2008, Lang. Resour. Evaluation.

[31]  G. Miller,et al.  Contextual correlates of semantic similarity , 1991 .

[32]  Howard Carter,et al.  A PRELIMINARY INVESTIGATION , 2010 .

[33]  Sabine Schulte im Walde.  Experiments on the Automatic Induction of German Semantic Verb Classes , 2006, CL.

[34]  Christiane Fellbaum,et al.  Book Reviews: WordNet: An Electronic Lexical Database , 1999, CL.