Coreference Resolution System using Maximum Entropy Classifier

نویسندگان

  • Wei-Peng Chen
  • Muyu Zhang
  • Bing Qin
چکیده

In this paper, we present our supervised learning approach to coreference resolution in ConLL corpus. The system relies on a maximum entropy-based classifier for pairs of mentions, and adopts a rich linguisitically motivated feature set, which mostly has been introduced by Soon et al (2001), and experiment with alternaive resolution process, preprocessing tools,and classifiers. We optimize the system’s performance for MUC (Vilain et al, 1995), BCUB (Bagga and Baldwin, 1998) and CEAF (Luo, 2005) .

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تاریخ انتشار 2011