Recognizing implicit discourse relations through abductive reasoning with large-scale lexical knowledge

Jun Sugiura, Naoya Inoue, Kentaro Inui

研究成果: Conference article査読

1 被引用数 (Scopus)

抄録

Discourse relation recognition is the task of identifying the semantic relationships between textual units. Conventional approaches to discourse relation recognition exploit surface information and syntactic information as machine learning features. However, the performance of these models is severely limited for implicit discourse relation recognition. In this paper, we propose an abductive theorem proving (ATP) approach for implicit discourse relation recognition. The contribution of this paper is that we give a detailed discussion of an ATP-based discourse relation recognition model with open-domain web texts.

本文言語English
ページ(範囲)76-87
ページ数12
ジャーナルCEUR Workshop Proceedings
1044
出版ステータスPublished - 2013 1 1
イベント1st Workshop on Natural Language Processing and Automated Reasoning, NLPAR 2013 - Co-located with 12th International Conference on Logic Programming and Nonmonotonic Reasoning, LPNMR 2013 - A Corunna, Spain
継続期間: 2013 9 15 → …

ASJC Scopus subject areas

  • Computer Science(all)

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