Papers by Zhenhua Fan

1 papers
PreCo: A Large-scale Dataset in Preschool Vocabulary for Coreference Resolution (D18-1)

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Challenge: Existing methods for coreference resolution are based on word2vec-like representations of entities.
Approach: They propose a large-scale English dataset for coreference resolution . they use 38K documents and 12.5M words from English-speaking preschoolers .
Outcome: The proposed dataset is more efficient with higher training-test overlap than OntoNotes . the study also shows that mention detection and clustering are more efficient on PreCo .

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