Predicate-Argument Structure-Based Textual Entailment Recognition System Exploiting Wide-Coverage Lexical Knowledge

Autor:	Tomohide Shibata, Sadao Kurohashi
Rok vydání:	2012
Předmět:	General Computer Science business.industry Computer science computer.software_genre Predicate (grammar) Linguistic analysis Lexical knowledge Recognition system Structure based Artificial intelligence business Textual entailment computer Natural language processing
Zdroj:	ACM Transactions on Asian Language Information Processing. 11:1-23
ISSN:	1558-3430 1530-0226
Popis:	This article proposes a predicate-argument structure based Textual Entailment Recognition system exploiting wide-coverage lexical knowledge. Different from conventional machine learning approaches where several features obtained from linguistic analysis and resources are utilized, our proposed method regards a predicate-argument structure as a basic unit, and performs the matching/alignment between a text and hypothesis. In matching between predicate-arguments, wide-coverage relations between words/phrases such as synonym and is-a are utilized, which are automatically acquired from a dictionary, Web corpus, and Wikipedia.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::ff49a3e4d8b55ef0681097fa669cc3ab https://doi.org/10.1145/2382593.2382598 Zobrazit plný text záznamu