University of Wolverhampton
Browse
Collection All
bullet
bullet
bullet
bullet
Listed communities
bullet
bullet
bullet
bullet
bullet
bullet
bullet
bullet
bullet
bullet
bullet
bullet
bullet

Wolverhampton Intellectual Repository and E-Theses > Research Institutes > Research Institute in Information and Language Processing > Computational Linguistics Group > Discovery of event entailment knowledge from text corpora

Please use this identifier to cite or link to this item: http://hdl.handle.net/2436/27900
    Del.icio.us     LinkedIn     Citeulike     Connotea     Facebook     Stumble it!



Title: Discovery of event entailment knowledge from text corpora
Authors: Pekar, Viktor
Citation: Computer Speech & Language, 22 (1): 1-16
Publisher: Elsevier
Journal: Computer Speech & Language
Issue Date: 2008
URI: http://hdl.handle.net/2436/27900
DOI: 10.1016/j.csl.2007.05.001
Additional Links: http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6WCW-4NS2GG9-1&_user=1644469&_rdoc=1&_fmt=&_orig=search&_sort=d&view=c&_acct=C000054077&_version=1&_urlVersion=0&_userid=1644469&md5=1476e51eca3b92da92fe97d9673ae682
Abstract: 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.
Type: Article
Language: en
Keywords: Lexical semantics
Lexical entailment
Local discourse
Coreference resolution
ISSN: 08852308
10958363
Appears in Collections: Computational Linguistics Group
Computational Linguistics Group

Files in This Item:

There are no files associated with this item.



All Items in WIRE are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Fairtrade - Guarantees a better deal for Third World Producers

University of Wolverhampton, Wulfruna Street, Wolverhampton, WV1 1LY

Course enquiries: 0800 953 3222, General enquiries: 01902 321000,
Email: enquiries@wlv.ac.uk | Freedom of Information | Disclaimer and copyright | Website feedback | The University as a charity

OR Logo Powered by Open Repository | Cookies