{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T04:24:53Z","timestamp":1750307093582,"version":"3.41.0"},"reference-count":24,"publisher":"Association for Computing Machinery (ACM)","issue":"4","license":[{"start":{"date-parts":[[2012,12,1]],"date-time":"2012-12-01T00:00:00Z","timestamp":1354320000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Transactions on Asian Language Information Processing"],"published-print":{"date-parts":[[2012,12]]},"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.1145\/2382593.2382598","type":"journal-article","created":{"date-parts":[[2012,12,5]],"date-time":"2012-12-05T18:55:48Z","timestamp":1354733748000},"page":"1-23","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Predicate-Argument Structure-Based Textual Entailment Recognition System Exploiting Wide-Coverage Lexical Knowledge"],"prefix":"10.1145","volume":"11","author":[{"given":"Tomohide","family":"Shibata","sequence":"first","affiliation":[{"name":"Kyoto University"}]},{"given":"Sadao","family":"Kurohashi","sequence":"additional","affiliation":[{"name":"Kyoto University"}]}],"member":"320","published-online":{"date-parts":[[2012,12]]},"reference":[{"key":"e_1_2_1_1_1","first-page":"1426","article-title":"On calculating word similarity using large text corpora","volume":"49","author":"Aizawa A.","year":"2008","journal-title":"IPSJ J."},{"volume-title":"Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP\u201904)","author":"Chklovski T.","key":"e_1_2_1_2_1"},{"key":"e_1_2_1_3_1","unstructured":"Curran J. 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