The PASCAL Recognising Textual Entailment Challenge

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3944 LNAI, Issue , 2006, Pages 177-190

  Dagan, Ido ^a   Glickman, Oren ^a   Magnini, Bernardo ^b  

^a BAR ILAN UNIVERSITY   (Israel)

^b ITC IRST   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BENCHMARKING; DATA ACQUISITION; LEARNING SYSTEMS; PREDICTIVE CONTROL SYSTEMS; SEMANTICS;

GENERIC RELEVANCE; MULTIPLE APPLICATIONS; RECOGNISING TEXTUAL ENTAILMENT; SEMANTIC EXPRESSION;

INFORMATION RETRIEVAL;

EID: 33745838229     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11736790_9     Document Type: Conference Paper

References (16)

1. Bacchus, F.: Representing and Reasoning with Probabilistic Knowledge, M.I.T. Press (1990).
2. Bar-Haim, R., Szpektor, I., Glickman O.: Definition and Analysis of Intermediate Entailment Levels. ACL-05 Workshop on Empirical Modeling of Semantic Equivalence and Entailment. (2005)
3. Chierchia, G., McConnell-Ginet, S.: Meaning and grammar: An introduction to semantics, 2nd. edition. Cambridge, MA: MIT Press (2001).
4. Condoravdi, C., Crouch, D., de Paiva, V., Stolle, R., Bobrow, D.G.: Entailment, intensionality and text understanding. HLT-NAACL Workshop on Text Meaning (2003)
5. Corley,C., Mihalcea, R.: Measuring the Semantic Similarity of Texts. Proceedings of the ACL Workshop on Empirical Modeling of Semantic Equivalence and Entailment, pages 1318, Ann Arbor, June 2005.
6. Dagan, I., Glickman, O.: Probabilistic Textual Entailment: Generic Applied Modeling of Language Variability. PASCAL workshop on Learning Methods for Text Understanding and Mining, 26 - 29 January (2004), Grenoble, France.
7. Glickman, O., Dagan, I., Koppel, M.: A Lexical Alignment Model for Probabilistic Textual Entailment. This Volums.
8. Halpern, J.Y.: An analysis of first-order logics of probability. Artificial Intelligence 46:311-350 (1990).
9. Keefe, R., Smith P. (ed.): Vagueness: A Reader. The MIT Press. 1997.
10. Lukasiewicz, J.: Selected Works, L. Borkowski Ed., North Holland, London, 1970.
11. Marsi, E., Krahmer, E.: Classification of Semantic Relations by Humans and Machines. Proceedings of the ACL Workshop on Empirical Modeling of Semantic Equivalence and Entailment, 2005.
12. Monz, C., de Rijke, M.: Light-Weight Entailment Checking for Computational Semantics, the third workshop on inference in computational semantics (ICoS-3). (2001)
13. Lucy Vanderwende and William B. Dolan: What Syntax can Contribute in the Entailment Task. This Volume.
14. Szpektor, I., Tanev, H., Dagan, I.,Coppola, B.: Scaling Web-based Acquisition of Entailment Relations. Empirical Methods in Natural Language Processing (EMNLP). (2004).
15. Zadeh, L.: Fuzzy sets. Information and Control, 8, 1965.
16. Zaenen, A., Karttunen, L., Crouch, R.: Local Textual Inference: Can it be Defined or Circumscribed?. Proceedings of the ACL Workshop on Empirical Modeling of Semantic Equivalence and Entailment, 2005.