Paper: Factorizing Complex Models: A Case Study In Mention Detection

ACL ID P06-1060
Title Factorizing Complex Models: A Case Study In Mention Detection
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2006
Authors

As natural language understanding re- search advances towards deeper knowledge modeling, the tasks become more and more complex: we are interested in more nu- anced word characteristics, more linguistic properties, deeper semantic and syntactic features. One such example, explored in this article, is the mention detection and recognition task in the Automatic Content Extraction project, with the goal of iden- tifying named, nominal or pronominal ref- erences to real-world entities—mentions— and labeling them with three types of in- formation: entity type, entity subtype and mention type. In this article, we investi- gate three methods of assigning these re- lated tags and compare them on several data sets. A system based on the methods presented in this article participated and ranked ...