Translation-oriented Word Sense Induction Based on Parallel Corpora

Word Sense Disambiguation (WSD) is an intermediate task that serves as a means to an end defined by the application in which it is to be used. However, different applications have varying disambiguation needs which should have an impact on the choice of the method and of the sense inventory used. The tendency towards application-oriented WSD becomes more and more evident, mostly because of the inadequacy of predefined sense inventories and the inefficacy of application-independent methods in accomplishing specific tasks. In this article, we present a data-driven method of sense induction, which combines contextual and translation information coming from a bilingual parallel training corpus. It consists of an unsupervised method that clusters semantically similar translation equivalents of source language (SL) polysemous words. The created clusters are projected on the SL words revealing their sense distinctions. Clustered equivalents describing a sense of a polysemous word can be considered as more or less commutable translations for an instance of the word carrying this sense. The resulting sense clusters can thus be used for WSD and sense annotation, as well as for lexical selection in translation applications.

[1]  Hwee Tou Ng,et al.  Exploiting Parallel Texts for Word Sense Disambiguation: An Empirical Study , 2003, ACL.

[2]  Hinrich Schütze,et al.  Automatic Word Sense Discrimination , 1998, Comput. Linguistics.

[3]  Zellig S. Harris,et al.  Distributional Structure , 1954 .

[4]  Nancy Ide,et al.  Fine-Grained Word Sense Disambiguation Based on Parallel Corpora, Word Alignment, Word Clustering and Aligned Wordnets , 2004, COLING.

[5]  Michel Simard,et al.  Statistical Translation Alignment with Compositionality Constraints , 2003, ParallelTexts@NAACL-HLT.

[6]  Rada Mihalcea,et al.  Automatic generation of a coarse grained WordNet , 2001, HTL 2001.

[7]  Hiroyuki Kaji,et al.  Unsupervised word sense disambiguation using bilingual comparable corpora , 2002, COLING 2002.

[8]  Roberto Navigli,et al.  Meaningful Clustering of Senses Helps Boost Word Sense Disambiguation Performance , 2006, ACL.

[9]  Hermann Ney,et al.  Statistical Machine Translation with Scarce Resources Using Morpho-syntactic Information , 2004, CL.

[10]  Lucia Specia,et al.  Multilingual versus Monolingual WSD , 2006 .

[11]  Helmut Schmidt,et al.  Probabilistic part-of-speech tagging using decision trees , 1994 .

[12]  Philipp Koehn,et al.  Europarl: A Parallel Corpus for Statistical Machine Translation , 2005, MTSUMMIT.

[13]  Gregory Grefenstette,et al.  Explorations in automatic thesaurus discovery , 1994 .

[14]  J. Firth,et al.  Papers in linguistics, 1934-1951 , 1957 .

[15]  Martha Palmer,et al.  The English all-words task , 2004, SENSEVAL@ACL.

[16]  Robert L. Mercer,et al.  A Statistical Approach to Sense Disambiguation in Machine Translation , 1991, HLT.

[17]  Adam Kilgarriff,et al.  "I Don’t Believe in Word Senses" , 1997, Comput. Humanit..

[18]  Ted Pedersen,et al.  Word Sense Discrimination by Clustering Contexts in Vector and Similarity Spaces , 2004, CoNLL.

[19]  J. Firth.  Papers in linguistics , 1958 .

[20]  Eneko Agirre,et al.  Semeval-2007 Task 2 : Evaluating Word Sense Induction and Discrimination , 2007 .

[21]  Stelios Piperidis,et al.  Building Parallel Corpora for eContent Professionals , 2004 .

[22]  Hiroyuki Kaji,et al.  Unsupervised Word-Sense Disambiguation Using Bilingual Comparable Corpora , 2002, IEICE Trans. Inf. Syst..

[23]  Jörg Tiedemann,et al.  Finding Synonyms Using Automatic Word Alignment and Measures of Distributional Similarity , 2006, ACL.

[24]  William B. Dolan,et al.  Word Sense Ambiguation: Clustering Related Senses , 1994, COLING.

[25]  Jean Véronis,et al.  HyperLex: lexical cartography for information retrieval , 2004, Comput. Speech Lang..

[26]  Márton Miháltz.  Towards A Hybrid Approach To Word-Sense Disambiguation In Machine Translation , 2005 .

[27]  Wim Peters,et al.  Automatic sense clustering in eurowordnet , 1998, LREC.

[28]  Yorick Wilks,et al.  The Grammar of Sense: Is word-sense tagging much more than part-of-speech tagging? , 1996, ArXiv.

[29]  Marianna Apidianaki.  Repérage de sens et désambiguïsation dans un contexte bilingue , 2007, JEPTALNRECITAL.

[30]  G. Miller,et al.  Contextual correlates of semantic similarity , 1991 .

[31]  Daphne Koller,et al.  Word-Sense Disambiguation for Machine Translation , 2005, HLT.

[32]  Ted Pedersen,et al.  The Senseval-3 Multilingual English-­Hindi lexical sample task , 2004, SENSEVAL@ACL.

[33]  Philip Resnik,et al.  Exploiting Hidden Meanings: Using Bilingual Text for Monolingual Annotation , 2004, CICLing.

[34]  Nancy Ide,et al.  Automatic Sense Tagging Using Parallel Corpora , 2001, NLPRS.

[35]  Adam Kilgarriff,et al.  Introduction to the special issue on evaluating word sense disambiguation systems , 2002, Natural Language Engineering.

[36]  Michael E. Lesk,et al.  Automatic sense disambiguation using machine readable dictionaries: how to tell a pine cone from an ice cream cone , 1986, SIGDOC '86.

[37]  Patrick Pantel,et al.  Discovering word senses from text , 2002, KDD.