Representations for category disambiguation

As it serves as a basis for POS tagging, category induction, and human category acquisition, we investigate the information needed to disambiguate a word in a local context, when using corpus categories. Specifically, we increase the recall of an error detection method by abstracting the word to be disambiguated to a representation containing information about some of its inherent properties, namely the set of categories it can potentially have. This work thus provides insights into the relation of corpus categories to categories derived from local contexts.

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