Paper: To Link or Not to Link? A Study on End-to-End Tweet Entity Linking

ACL ID N13-1122
Title To Link or Not to Link? A Study on End-to-End Tweet Entity Linking
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2013
Authors

Information extraction from microblog posts is an important task, as today microblogs cap- ture an unprecedented amount of information and provide a view into the pulse of the world. As the core component of information extrac- tion, we consider the task of Twitter entity linking in this paper. In the current entity linking literature, mention detection and entity disambiguation are fre- quently cast as equally important but distinct problems. However, in our task, we find that mention detection is often the performance bottleneck. The reason is that messages on micro-blogs are short, noisy and informal texts with little context, and often contain phrases with ambiguous meanings. To rigorously address the Twitter entity link- ing problem, we propose a structural SVM algorithm for entity li...