Projecting parameters for multilingual word sense disambiguation

We report in this paper a way of doing Word Sense Disambiguation (WSD) that has its ori-gin in multilingual MT and that is cognizant of the fact that parallel corpora, wordnets and sense annotated corpora are scarce re-sources. With respect to these resources, lan-guages 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 lan-guage 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 ap-proximately 75 % (F1-score) for three lan-guages in two different domains establish the fact that within a domain it is possible to cir-cumvent the problem of scarcity of resources by projecting parameters like sense distribu-tions, corpus-co-occurrences, conceptual dis-tance, etc. from one language to another