Discovery of event entailment knowledge from text corpora

Event entailment is knowledge that may prove useful for a variety of applications dealing with inferencing over events described in natural language texts. In this paper, we propose a method for automatic discovery of pairs of verbs related by entailment, such as X buy Y X own Y and appoint X as Y X become Y. In contrast to previous approaches that make use of lexico-syntactic patterns and distributional evidence, the underlying assumption of our method is that the implication of one event by another manifests itself in the regular co-occurrence of the two corresponding verbs within locally coherent text. Based on the analogy with the problem of learning selectional preferences Resnik's [Resnik, P., 1993. Selection and information: a class-based approach to lexical relationships, Ph.D. Thesis, University of Pennsylvania] association strength measure is used to score the extracted verb pairs for asymmetric association in order to discover the direction of entailment in each pair. In our experimental evaluation, we examine the effect that various local discourse indicators produce on the accuracy of this model of entailment. After that we carry out a direct evaluation of the verb pairs against human subjects' judgements and extrinsically evaluate the pairs on the task of noun phrase coreference resolution.

[1]  Marti A. Hearst.  Automatic Acquisition of Hyponyms from Large Text Corpora , 1992, COLING.

[2]  Carl Pollard,et al.  A Centering Approach to Pronouns , 1987, ACL.

[3]  Ido Dagan,et al.  The Distributional Inclusion Hypotheses and Lexical Entailment , 2005, ACL.

[4]  Scott Weinstein,et al.  Centering: A Framework for Modeling the Local Coherence of Discourse , 1995, CL.

[5]  Ido Dagan,et al.  Similarity-Based Models of Word Cooccurrence Probabilities , 1998, Machine Learning.

[6]  Mirella Lapata,et al.  Modeling Local Coherence: An Entity-Based Approach , 2005, ACL.

[7]  P. Resnik.  Selection and information: a class-based approach to lexical relationships , 1993 .

[8]  Patrick Pantel,et al.  Discovery of inference rules for question-answering , 2001, Natural Language Engineering.

[9]  Éric Gaussier,et al.  Lexical Entailment for Information Retrieval , 2006, ECIR.

[10]  Regina Barzilay,et al.  Inferring Strategies for Sentence Ordering in Multidocument News Summarization , 2002, J. Artif. Intell. Res..

[11]  Satoshi Sekine,et al.  Automatic paraphrase acquisition from news articles , 2002 .

[12]  David J. Weir,et al.  Characterising Measures of Lexical Distributional Similarity , 2004, COLING.

[13]  Patrick Pantel,et al.  Global Path-Based Refinement of Noisy Graphs Applied to Verb Semantics , 2005, IJCNLP.

[14]  Marius Pasca,et al.  Finding Instance Names and Alternative Glosses on the Web: WordNet Reloaded , 2005, CICLing.

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

[16]  Timo Järvinen,et al.  A non-projective dependency parser , 1997, ANLP.

[17]  Vasile Rus,et al.  Logic Form Transformation of WordNet and its Applicability to Question Answering , 2001, ACL.

[18]  Alex Lascarides,et al.  Logics of Conversation , 2005, Studies in natural language processing.

[19]  David Baxter,et al.  On the Effective Use of Cyc in a Question Answering System , 2005 .

[20]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[21]  G. Miller,et al.  A Semantic Network of English Verbs , 1998 .

[22]  Patrick Pantel,et al.  VerbOcean: Mining the Web for Fine-Grained Semantic Verb Relations , 2004, EMNLP.

[23]  Fabio Massimo Zanzotto,et al.  Discovering Asymmetric Entailment Relations between Verbs Using Selectional Preferences , 2006, ACL.

[24]  Eduard H. Hovy,et al.  Learning surface text patterns for a Question Answering System , 2002, ACL.

[25]  Roxana Gîrju,et al.  Automatic Detection of Causal Relations for Question Answering , 2003, ACL 2003.

[26]  J. Hobbs.  On the coherence and structure of discourse , 1985 .

[27]  Bonnie L. Webber,et al.  Questions and Answers: Theoretical and Applied Perspectives , 2007, J. Appl. Log..

[28]  Kentaro Torisawa.  Acquiring Inference Rules with Temporal Constraints by Using Japanese Coordinated Sentences and Noun-Verb Co-occurrences , 2006, HLT-NAACL.

[29]  Simone Paolo Ponzetto,et al.  Exploiting Semantic Role Labeling, WordNet and Wikipedia for Coreference Resolution , 2006, NAACL.

[30]  Claire Gardent,et al.  Improving Machine Learning Approaches to Coreference Resolution , 2002, ACL.

[31]  Yuji Matsumoto,et al.  What Kinds and Amounts of Causal Knowledge Can Be Acquired from Text by Using Connective Markers as Clues? , 2003, Discovery Science.

[32]  Zellig S. Harris,et al.  Mathematical structures of language , 1968, Interscience tracts in pure and applied mathematics.

[33]  Mark Stevenson,et al.  The Reuters Corpus Volume 1 -from Yesterday’s News to Tomorrow’s Language Resources , 2002, LREC.

[34]  James Pustejovsky,et al.  Machine Learning of Temporal Relations , 2006, ACL.

[35]  Ido Dagan,et al.  The Third PASCAL Recognizing Textual Entailment Challenge , 2007, ACL-PASCAL@ACL.

[36]  Jacob Cohen.  A Coefficient of Agreement for Nominal Scales , 1960 .

[37]  Ido Dagan,et al.  Integrating Pattern-Based and Distributional Similarity Methods for Lexical Entailment Acquisition , 2006, ACL.

[38]  Richard Power,et al.  Optimizing Referential Coherence in Text Generation , 2004, CL.

[39]  Mirella Lapata,et al.  Probabilistic Text Structuring: Experiments with Sentence Ordering , 2003, ACL.

[40]  Hwee Tou Ng,et al.  A Machine Learning Approach to Coreference Resolution of Noun Phrases , 2001, CL.

[41]  Dekang Lin,et al.  Automatic Retrieval and Clustering of Similar Words , 1998, ACL.

[42]  Daniel Marcu,et al.  Syntax-based Alignment of Multiple Translations: Extracting Paraphrases and Generating New Sentences , 2003, NAACL.

[43]  Chris Mellish,et al.  Evaluating Centering-Based Metrics of Coherence , 2004, ACL.

[44]  Inderjeet Mani,et al.  Temporally Anchoring and Ordering Events in News , 2004 .

[45]  Sanda M. Harabagiu,et al.  Methods for Using Textual Entailment in Open-Domain Question Answering , 2006, ACL.

[46]  Doug Downey,et al.  Web-scale information extraction in knowitall: (preliminary results) , 2004, WWW '04.

[47]  Constantin Orasan,et al.  NPs for Events: Experiments in Coreference Annotation , 2006, LREC.

[48]  Ehud Reiter,et al.  Book Reviews: Building Natural Language Generation Systems , 2000, CL.