Cited By
View all- Castillo JEstrella P(2012)Semantic textual similarity for MT evaluationProceedings of the Seventh Workshop on Statistical Machine Translation10.5555/2393015.2393020(52-58)Online publication date: 7-Jun-2012
SAGAN: a machine translation approach for cross-lingual textual entailment
Abstract
This paper describes our participation in the task denominated Cross-Lingual Textual Entailment (CLTE) for content synchronization. We represent an approach to CLTE using machine translation to tackle the problem of multilinguality. Our system resides on machine learning and in the use of WordNet as semantic source knowledge. Results are very promising always achieving results above mean score.
References
[1]
Ido Dagan, Oren Glickman and Bernardo Magnini. 2006. The PASCAL Recognising Textual Entailment Challenge. In Quiñonero-Candela, J.; Dagan, I.; Magnini, B.; d'Alché-Buc, F. (Eds.) Machine Learning Challenges. Lecture Notes in Computer Science, Vol. 3944, pp. 177--190, Springer.
[2]
M. Negri, A. Marchetti, Y. Mehdad, L. Bentivogli, and D. Giampiccolo. 2012. Semeval-2012 Task 8: Cross-lingual Textual Entailment for Content Synchronization. In Proceedings of the 6th International Workshop on Semantic Evaluation (SemEval 2012).
[3]
L. Bentivogli, P. Clark, I. Dagan, H. T. Dang, and D. Giampiccolo. 2010. The Sixth PASCAL Recognizing Textual Entailment Challenge. In TAC 2010 Workshop Proceedings, NIST, Gaithersburg, MD, USA.
[4]
Y. Mehdad, M. Negri, and M. Federico. 2010. Towards Cross-Lingual Textual Entailment. In Proceedings of NAACL-HLT 2010.
[5]
Eneko Agirre, Daniel Cer, Mona Diab and Aitor Gonzalez-Agirre. 2012. SemEval-2012 Task 6: A Pilot on Semantic Textual Similarity. In Proceedings of the 6th International Workshop on Semantic Evalua-tion (SemEval 2012), in conjunction with the First Joint Conference on Lexical and Computational Semantics (*SEM2012).
[6]
Bentivogli, Luisa, Dagan Ido, Dang Hoa, Giampiccolo, Danilo, Magnini Bernardo. 2009. The Fifth PASCAL RTE Challenge. In: Proceedings of the Text Analysis Conference.
[7]
Fellbaum C. 1998. WordNet: An Electronic Lexical Database, volume 1. MIT Press.
[8]
Castillo Julio. 2011. A WordNet-based semantic approach to textual entailment and cross-lingual textual entailment. International Journal of Machine Learning and Cybernetics - Springer, Volume 2, Number 3.
[9]
Castillo Julio and Cardenas Marina. 2010. Using sentence semantic similarity based on WordNet in recognizing textual entailment. Iberamia 2010. In LNCS, vol 6433. Springer, Heidelberg, pp 366--375.
[10]
Castillo Julio. 2010. A semantic oriented approach to textual entailment using WordNet-based measures. MICAI 2010. LNCS, vol 6437. Springer, Heidelberg, pp 44--55.
[11]
Castillo Julio. 2010. Using machine translation systems to expand a corpus in textual entailment. In: Proceedings of the Icetal 2010. LNCS, vol 6233, pp 97--102.
[12]
M. Negri, L. Bentivogli, Y. Mehdad, D. Giampiccolo, and A. Marchetti. 2011. Divide and Conquer: Crowdsourcing the Creation of Cross-Lingual Textual Entailment Corpora. In Proceedings of the Conference on Empirical Methods in Natural. EMNLP 2011.
[13]
Resnik P. 1995. Information content to evaluate semantic similarity in a taxonomy. In: Proceedings of IJCAI 1995, pp 448--453.
[14]
Castillo Julio, Cardenas Marina. 2011. An Approach to Cross-Lingual Textual Entailment using Online Machine Translation Systems. Polibits Journal. Vol 44.
[15]
Castillo Julio and Estrella Paula. 2012. Semantic Textual Similarity for MT evaluation. NAACL 2012 Seventh Workshop on Statistical Machine Translation. WMT 2012, Montreal, Canada.
[16]
Lin D. 1997. An information-theoretic definition of similarity. In: Proceedings of Conference on Machine Learning, pp 296--304.
[17]
Jiang J, Conrath D. 1997. Semantic similarity based on corpus statistics and lexical taxonomy. In: Proceedings of the ROCLINGX.
[18]
Pirro G., Seco N. 2008. Design, implementation and evaluation of a new similarity metric combining feature and intrinsic information content. In: ODBASE 2008, Springer LNCS.
[19]
Wu Z, Palmer M. 1994. Verb semantics and lexical selection. In: Proceedings of the 32nd ACL 916.
[20]
Leacock C, Chodorow M. 1998. Combining local context and WordNet similarity for word sense identification. MIT Press, pp 265--283.
[21]
Hirst G, St-Onge D. 1998. Lexical chains as representations of context for the detection and correction of malapropisms. MIT Press, pp 305--332.
[22]
Banerjee S, Pedersen T. 2002. An adapted lesk algorithm for word sense disambiguation using WordNet. In: Proceeding of CICLING-02.
[23]
William B. Dolan and Chris Brockett. 2005. Automatically Constructing a Corpus of Sentential Paraphrases. Third International Workshop on Paraphrasing (IWP2005). Asia Federation of Natural Language Processing.
[24]
Castillo Julio and Estrella Paula. 2012. SAGAN: An approach to Semantic Textual Similarity based on Textual Entailment. In Proceedings of the 6th International Workshop on Semantic Evaluation (SemEval 2012), in conjunction with the First Joint Conference on Lexical and Computational Semantics (*SEM2012).
[25]
Mehdad Y., M. Negri, and M. Federico. 2011. Using Parallel Corpora for Cross-lingual Textual Entailment. In Proceedings of ACL-HLT 2011.
- SAGAN: a machine translation approach for cross-lingual textual entailment
Recommendations
Toward an Effective Igbo Part-of-Speech Tagger
Part-of-speech (POS) tagging is a well-established technology for most Western European languages and a few other world languages, but it has not been evaluated on Igbo, an agglutinative African language. This article presents POS tagging experiments ...
SemEval-2010 task 3: cross-lingual word sense disambiguation
SEW '09: Proceedings of the Workshop on Semantic Evaluations: Recent Achievements and Future DirectionsWe propose a multilingual unsupervised Word Sense Disambiguation (WSD) task for a sample of English nouns. Instead of providing manually sensetagged examples for each sense of a polysemous noun, our sense inventory is built up on the basis of the ...
Hindi Word Sense Disambiguation Using Lesk Approach on Bigram and Trigram Words
AICTC '16: Proceedings of the International Conference on Advances in Information Communication Technology & ComputingWord Sense Disambiguation (WSD) is a vital task which provides the definition of particular words according to their sense or according to given context. Lesk algorithm is originally based on the gloss overlap that can be observed as the measure, ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
Publisher
Association for Computational Linguistics
United States
Publication History
Published: 07 June 2012
Qualifiers
- Research-article
Acceptance Rates
Overall Acceptance Rate 8 of 31 submissions, 26%
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- View Citations1Total Citations
- 109Total Downloads
- Downloads (Last 12 months)61
- Downloads (Last 6 weeks)17
Reflects downloads up to 19 Nov 2024
Other Metrics
Citations
Cited By
View all- Castillo JEstrella P(2012)Semantic textual similarity for MT evaluationProceedings of the Seventh Workshop on Statistical Machine Translation10.5555/2393015.2393020(52-58)Online publication date: 7-Jun-2012
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in