Projecting parameters for multilingual word sense disambiguation

Abstract

We report in this paper a way of doing Word Sense Disambiguation (WSD) that has its origin in multilingual MT and that is cognizant of the fact that parallel corpora, wordnets and sense annotated corpora are scarce resources. With respect to these resources, languages show different levels of readiness; however a more resource fortunate language can help a less resource fortunate language. Our WSD method can be applied to a language even when no sense tagged corpora for that language is available. This is achieved by projecting wordnet and corpus parameters from another language to the language in question. The approach is centered around a novel synset based multilingual dictionary and the empirical observation that within a domain the distribution of senses remains more or less invariant across languages. The effectiveness of our approach is verified by doing parameter projection and then running two different WSD algorithms. The accuracy values of approximately 75% (F1-score) for three languages in two different domains establish the fact that within a domain it is possible to circumvent the problem of scarcity of resources by projecting parameters like sense distributions, corpus-co-occurrences, conceptual distance, etc. from one language to another.

Wiki sense bag creation using multilingual word sense disambiguation

“…The role of WSD for multilingual scenario of NLP text was surveyed using English-Spanish languages [18]. WSD in multilingual machine translation (MT) is based on the concept that resource full language helps a resource low language by projecting parameters like sense distributions, and corpus cooccurrences [19]. The accuracy observed was 75% for three languages with domain specific corpus.…”

Word Sense Disambiguation Using Wikipedia

“…Li and Li (2004) introduced a bilingual bootstrapping approach, in which starting with indomain corpora in two different languages, English and Chinese, word translations are automatically disambiguated using information iteratively drawn from the bilingual corpora. Khapra et al (2009; proposed another bilingual bootstrapping approach, in which they used an aligned multilingual dictionary and bilingual corpora to show how resource deprived languages can benefit from a resource rich language. They introduced a technique called parameter projections, in which parameters learned using both aligned multilingual Wordnet and bilingual corpora are projected from one language to another language to improve on existing WSD methods.…”

Survey on Indian CLIR and MT systems in Marathi Language

“…Khapra et al [11] proposed a WSD method that can be applied to a language even when no sense tagged corpora for that language is available. This is achieved by projecting wordnet and corpus parameters from another language to the language in question.…”