Paper: Coreference Resolution Using Semantic Relatedness Information from Automatically Discovered Patterns

ACL ID P07-1067
Title Coreference Resolution Using Semantic Relatedness Information from Automatically Discovered Patterns
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2007
Authors

Semantic relatedness is a very important fac- tor for the coreference resolution task. To obtain this semantic information, corpus- based approaches commonly leverage pat- terns that can express a specific semantic relation. The patterns, however, are de- signed manually and thus are not necessar- ily the most effective ones in terms of ac- curacy and breadth. To deal with this prob- lem, in this paper we propose an approach that can automatically find the effective pat- terns for coreference resolution. We explore how to automatically discover and evaluate patterns, and how to exploit the patterns to obtain the semantic relatedness information. The evaluation on ACE data set shows that the pattern based semantic information is helpful for coreference resolution.