Hypothesis transformation and semantic variability rules used in recognizing textual entailment

Proceedings of the Annual Meeting of the Association for Computational Linguistics

Volumn , Issue , 2007, Pages 125-130

  Iftene, Adrian ^a   Balahur Dobrescu, Alexandra ^a  

^a ALEXANDRU IOAN CUZA UNIVERSITY OF IASI   (Romania)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL LINGUISTICS; NATURAL LANGUAGE PROCESSING SYSTEMS; TREES (MATHEMATICS);

BACKGROUND KNOWLEDGE; DISTANCE ALGORITHM; GRAMMAR RULES; RECOGNIZING TEXTUAL ENTAILMENTS; SEMANTICS KNOWLEDGE; TREE EDIT DISTANCE; WIKIPEDIA; WORDNET;

SEMANTICS;

EID: 84927581813     PISSN: 0736587X     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (5)

1. Dagan, I., Glickman, O., and Magnini, B. 2006. The PASCAL Recognising Textual Entailment Challenge. In Quiñonero-Candela et al., editors, MLCW 2005, LNAI Volume 3944, pages 177-190. Springer-Verlag.
2. Fellbaum, C. 1998. WordNet: An Electronic Lexical Database. MIT Press, Cambridge, Mass.
3. Kouylekov, M. and Magnini, B. 2005. Recognizing Textual Entailment with Tree Edit Distance Algorithms. In Proceedings of the First Challenge Workshop Recognising Textual Entailment, Pages 17-20, 25–28 April, 2005, Southampton, U.K.
4. Lin, D. 1998. Dependency-based Evaluation of MINIPAR. In Workshop on the Evaluation of Parsing Systems, Granada, Spain, May, 1998.
5. Lin, D., and Pantel, P. 2001. DIRT - Discovery of Inference Rules from Text. In Proceedings of ACM Conference on Knowledge Discovery and Data Mining (KDD-01). pp. 323-328. San Francisco, CA.