Laxmi Kashyap

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Department of Computer Science and Engineering Indian Institute of Technology Bombay, Mumbai India {manish, mahesh, pb,pandey,yupu}@cse.iitb.ac.in Abstract Word Sense Disambiguation (WSD) is defined as the task of finding the correct sense of a word in a specific context. This is crucial for applications like Machine Translation and Information Extraction.(More)
Word Sense Disambiguation (WSD) is one of the open problems in the area of natural language processing. Various supervised, unsupervised and knowledge based approaches have been proposed for automatically determining the sense of a word in a particular context. It has been observed that such approaches often find it difficult to beat the WordNet First Sense(More)
Bilingual corpora play an important role as resources not only for machine translation research and development but also for studying tasks in comparative linguistics. Manual annotation of word alignments is of significance to provide a gold-standard for developing and evaluating machine translation models and comparative linguistics tasks. This paper(More)
This paper reports the work of creating bilingual mappings in English for certain synsets of Hindi wordnet, the need for doing this, the methods adopted and the tools created for the task. Hindi wordnet, which forms the foundation for other Indian language wordnets, has been linked to the English WordNet. To maximize linkages, an important strategy of using(More)
In this survey paper, we have taken the problem as “Development of an approach for disambiguating ambiguous Hindi postposition”. Word Sense Disambiguation (WSD) refers to the resolution of lexical semantic ambiguity and its goal is to attribute the correct senses to words in a given context. WSD is a most challenging problem in the area of NLP. We have(More)
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