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We present MSDA (Major Senses Discovery Algorithm) – a development over the context vector approach to (noun) sense discrimination [20, 24] that uses attributes and values instead of word features to cluster contexts, and does not require for the number of senses to be fixed beforehand. The algorithm achieves a precision of 89% on a dataset including both ambiguous and non-ambiguous nouns, twice that of previous algorithms.
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