Abstract
Verbs represent a way in which ontological relationships between concepts and instances are expressed in natural language utterances. Moreover, an organized network of semantically related verbs can play a crucial role in applications. For example, if a Question-Answering system could exploit the direction of the entailment relation win → play, it may expand the question “Who played against Liverpool?” with “X won against Liverpool” and it may avoid the expansion of “Who won against Liverpool?” in “X played against Liverpool” that would be wrong. In this paper, we present a survey of the methods proposed to extract verb relations in corpora. These methods can be divided in two classes: those using the Harris distributional hypothesis and those based on point-wise assertions. These methods are analysed and compared.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Jacquemin, C.: Spotting and Discovering Terms through Natural Language Processing. Massachusetts Institue of Technology, Cambrige, Massachussetts, USA (2001)
In: MUC 1997: Proceedings of the seventh message understanding conference (MUC 1997). Columbia, MD, Morgan Kaufmann (1997)
Pazienza, M.T. (ed.): Information Extraction. A Multidisciplinary Approach to an Emerging Information Technology. LNCS (LNAI), vol. 1299. Springer, Heidelberg (1997)
Morin, E.: Extraction de liens sémantiques entre termes à partir de corpus de textes techniques. PhD thesis, Univesité de Nantes, Faculté des Sciences et de Techniques (1999)
Harris, Z.: Distributional structure. In: Katz, J.J., Fodor, J.A. (eds.) The Philosophy of Linguistics. Oxford University Press, New York (1964)
Robison, H.R.: Computer-detectable semantic structures. Information Storage and Retrieval 6, 273–288 (1970)
Miller, G.A.: WordNet: A lexical database for English. Communications of the ACM 38, 39–41 (1995)
Glickman, O., Dagan, I.: Identifying lexical paraphrases from a single corpus: A case study for verbs. In: Proceedings of the International Conference Recent Advances of Natural Language Processing (RANLP 2003), Borovets, Bulgaria (2003)
Lin, D., Pantel, P.: DIRT-discovery of inference rules from text. In: Proc. of the ACM Conference on Knowledge Discovery and Data Mining (KDD 2001), San Francisco, CA (2001)
Church, K.W., Hanks, P.: Word association norms, mutual information and lexicography. In: Proceedings of the 27th Annual Meeting of the Association for Computational Linguistics (ACL), Vancouver, Canada (1989)
Hearst, M.A.: Automatic acquisition of hyponyms from large text corpora. In: Proceedings of the 15th International Conference on Computational Linguistics (CoLing 1992), Nantes, France (1992)
Ravichandran, D., Hovy, E.: Learning surface text patterns for a question answering system. In: Proceedings of the 40th ACL Meeting, Philadelphia, Pennsilvania (2002)
Szpektor, I., Tanev, H., Dagan, I., Coppola, B.: Scaling web-based acquisition of entailment relations. In: Proceedings of the 2004 Conference on Empirical Methods in Natural Language Processing, Barcellona, Spain (2004)
Zanzotto, F.M., Pazienza, M.T., Pennacchiotti, M.: Discovering entailment relations using textual entailment patterns. In: Proc. of the ACL Workshop on Empirical Modeling of Semantic Equivalence and Entailment, Ann Arbor, Michigan, Association for Computational Linguistics, pp. 13–18 (2005)
Chklovski, T., Pantel, P.: VerbOCEAN: Mining the web for fine-grained semantic verb relations. In: Proceedings of the 2004 Conference on Empirical Methods in Natural Language Processing, Barcellona, Spain (2004)
Glickman, O., Dagan, I., Koppel, M.: Web based probabilistic textual entailment. In: Proceedings of the 1st Pascal Challenge Workshop, Southampton, UK (2005)
Resnik, P.: Selection and Information: A Class-Based Approach to Lexical Relationships. PhD thesis, Department of Computer and Information Science, University of Pennsylvania (1993)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Pazienza, M.T., Pennacchiotti, M., Zanzotto, F.M. (2006). Discovering Verb Relations in Corpora: Distributional Versus Non-distributional Approaches. In: Ali, M., Dapoigny, R. (eds) Advances in Applied Artificial Intelligence. IEA/AIE 2006. Lecture Notes in Computer Science(), vol 4031. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11779568_111
Download citation
DOI: https://doi.org/10.1007/11779568_111
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-35453-6
Online ISBN: 978-3-540-35454-3
eBook Packages: Computer ScienceComputer Science (R0)