Paper: Combining Linguistic Features With Weighted Bayesian Classifier For Temporal Reference Processing

ACL ID C04-1101
Title Combining Linguistic Features With Weighted Bayesian Classifier For Temporal Reference Processing
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2004
Authors

Temporal reference is an issue of determining how events relate to one another. Determining temporal relations relies on the combination of the information, which is explicit or implicit in a language. This paper reports a computational model for determining temporal relations in Chinese. The model takes into account the ef- fects of linguistic features, such as tense/aspect, temporal connectives, and discourse structures, and makes use of the fact that events are repre- sented in different temporal structures. A ma- chine learning approach, Weighted Bayesian Classifier, is developed to map their combined effects to the corresponding relations. An em- pirical study is conducted to investigate differ- ent combination methods, including lexical- based, grammatical-based, and role-based metho...