A Discriminative Approach to Japanese Zero Anaphora Resolution with Large-scale Lexicalized Case Frames

要旨

We present a discriminative model for Japanese zero anaphora resolution that simultaneously determines an appropriate case frame for a given predicate and its predicate-argument structure. Our model is based on a log linear framework, and exploits lexical features obtained from a large raw corpus, as well as non-lexical features obtained from a relatively small annotated corpus. We report the results of zero anaphora resolution on Web text and demonstrate the effectiveness of our approach. In addition, we also investigate the relative importance of each feature for resolving zero anaphora in Web text.

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