TY - GEN
T1 - JU-CSE-NLP
T2 - 1st Joint Conference on Lexical and Computational Semantics, *SEM 2012
AU - Neogi, Snehasis
AU - Pakray, Partha
AU - Bandyopadhyay, Sivaji
AU - Gelbukh, Alexander
N1 - Publisher Copyright:
© 2012 Association for Computational Linguistics.
PY - 2012
Y1 - 2012
N2 - This article presents the experiments carried out at Jadavpur University as part of the participation in Cross-lingual Textual Entailment for Content Synchronization (CLTE) of task 8 @ Semantic Evaluation Exercises (SemEval-2012). The work explores cross-lingual textual entailment as a relation between two texts in different languages and proposes different measures for entailment decision in a four way classification tasks (forward, backward, bidirectional and no-entailment). We set up different heuristics and measures for evaluating the entailment between two texts based on lexical relations. Experiments have been carried out with both the text and hypothesis converted to the same language using the Microsoft Bing translation system. The entailment system considers Named Entity, Noun Chunks, Part of speech, N-Gram and some text similarity measures of the text pair to decide the entailment judgments. Rules have been developed to encounter the multi way entailment issue. Our system decides on the entailment judgment after comparing the entailment scores for the text pairs. Four different rules have been developed for the four different classes of entailment. The best run is submitted for Italian-English language with accuracy 0.326.
AB - This article presents the experiments carried out at Jadavpur University as part of the participation in Cross-lingual Textual Entailment for Content Synchronization (CLTE) of task 8 @ Semantic Evaluation Exercises (SemEval-2012). The work explores cross-lingual textual entailment as a relation between two texts in different languages and proposes different measures for entailment decision in a four way classification tasks (forward, backward, bidirectional and no-entailment). We set up different heuristics and measures for evaluating the entailment between two texts based on lexical relations. Experiments have been carried out with both the text and hypothesis converted to the same language using the Microsoft Bing translation system. The entailment system considers Named Entity, Noun Chunks, Part of speech, N-Gram and some text similarity measures of the text pair to decide the entailment judgments. Rules have been developed to encounter the multi way entailment issue. Our system decides on the entailment judgment after comparing the entailment scores for the text pairs. Four different rules have been developed for the four different classes of entailment. The best run is submitted for Italian-English language with accuracy 0.326.
UR - http://www.scopus.com/inward/record.url?scp=84891924016&partnerID=8YFLogxK
M3 - Contribución a la conferencia
AN - SCOPUS:84891924016
T3 - *SEM 2012 - 1st Joint Conference on Lexical and Computational Semantics
SP - 689
EP - 695
BT - Proceedings of the 6th International Workshop on Semantic Evaluation, SemEval 2012
PB - Association for Computational Linguistics (ACL)
Y2 - 7 June 2012 through 8 June 2012
ER -