Paper: Evaluating Automated And Manual Acquisition Of Anaphora Resolution Strategies

ACL ID P95-1017
Title Evaluating Automated And Manual Acquisition Of Anaphora Resolution Strategies
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 1995
Authors

We describe one approach to build an au- tomatically trainable anaphora resolution system. In this approach, we use Japanese newspaper articles tagged with discourse information as training examples for a ma- chine learning algorithm which employs the C4.5 decision tree algorithm by Quin- lan (Quinlan, 1993). Then, we evaluate and compare the results of several variants of the machine learning-based approach with those of our existing anaphora resolu- tion system which uses manually-designed knowledge sources. Finally, we compare our algorithms with existing theories of anaphora, in particular, Japanese zero pro- nouns.