Abstract
This paper presents corpus-based approach to word sense disambiguation where decision tree ssigns sense to an ambiguous word based on the bigrams that occur nearby. This approach is evaluated using the sense-tagged corpora from the 1998 SENSEVAL word sense disambiguation exercise. It is more ccurate than the verage results reported for 30 of 36 words, and is more accurate than the best results for 19 of 36 words.
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Pedersen, T. (2001). Lexical Semantic Ambiguity Resolution with Bigram-Based Decision Trees. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2001. Lecture Notes in Computer Science, vol 2004. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44686-9_16
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DOI: https://doi.org/10.1007/3-540-44686-9_16
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