Baldwin, Timothy, Su Nam Kim, Francis Bond, Sanae Fujita, David Martinez and Takaaki Tanaka (2008) MRD-based Word Sense Disambiguation: Further Extending Lesk, In Proceedings of the Third International Joint Conference on Natural Language Processing (IJCNLP 2008), Hyderabad, India
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چکیده
This paper reconsiders the task of MRDbased word sense disambiguation, in extending the basic Lesk algorithm to investigate the impact onWSD performance of different tokenisation schemes, scoring mechanisms, methods of gloss extension and filtering methods. In experimentation over the Lexeed Sensebank and the Japanese Senseval2 dictionary task, we demonstrate that character bigrams with sense-sensitive gloss extension over hyponyms and hypernyms enhances WSD performance.
منابع مشابه
MRD-based Word Sense Disambiguation: Further Extending Lesk
This paper reconsiders the task of MRDbased word sense disambiguation, in extending the basic Lesk algorithm to investigate the impact onWSD performance of different tokenisation schemes, scoring mechanisms, methods of gloss extension and filtering methods. In experimentation over the Lexeed Sensebank and the Japanese Senseval2 dictionary task, we demonstrate that character bigrams with sense-s...
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This paper reconsiders the task of MRDbased word sense disambiguation, in extending the basic Lesk algorithm to investigate the impact onWSD performance of different tokenisation schemes, scoring mechanisms, methods of gloss extension and filtering methods. In experimentation over the Lexeed Sensebank and the Japanese Senseval2 dictionary task, we demonstrate that character bigrams with sense-s...
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In this paper we provide benchmark results for two classes of methods used in interpreting noun compounds (NCs): semantic similarity-based methods and their hybrids. We evaluate the methods using 7-way and binary class data from the nominal pair interpretation task of SEMEVAL-2007.1 We summarize and analyse our results, with the intention of providing a framework for benchmarking future researc...
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In this paper, we investigate word sense distributions in noun compounds (NCs). Our primary goal is to disambiguate the word sense of component words in NCs, based on investigation of “semantic collocation” between them. We use sense collocation and lexical substitution to build supervised and unsupervised word sense disambiguation (WSD) classifiers, and show our unsupervised learner to be supe...
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