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Lexical Features in Coreference Resolution: To be Used With Caution

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arxiv 1704.06779 v1 pith:EOYVFCVI submitted 2017-04-22 cs.CL

classification cs.CL
keywords coreferencefeatureslexicalresolversresolutionspecificstate-of-the-artthey
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Lexical features are a major source of information in state-of-the-art coreference resolvers. Lexical features implicitly model some of the linguistic phenomena at a fine granularity level. They are especially useful for representing the context of mentions. In this paper we investigate a drawback of using many lexical features in state-of-the-art coreference resolvers. We show that if coreference resolvers mainly rely on lexical features, they can hardly generalize to unseen domains. Furthermore, we show that the current coreference resolution evaluation is clearly flawed by only evaluating on a specific split of a specific dataset in which there is a notable overlap between the training, development and test sets.

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  1. Mogrifier LSTM

    cs.CL 2019-09 accept novelty 6.0 of 10

    Mogrifier LSTM, which applies repeated mutual gating between the input and previous hidden state, outperforms the LSTM on PTB, Wikitext-2, Enwik8, and MWC language modeling.

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