Coreference Resolution System using Maximum Entropy Classifier
Weipeng Chen, Muyu Zhang, Bing Qin · 2011
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 M-UC (Vilain et al, 1995), BCUB (Bagga and