Paper: Extracting Opinion Expressions with semi-Markov Conditional Random Fields

ACL ID D12-1122
Title Extracting Opinion Expressions with semi-Markov Conditional Random Fields
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2012
Authors

Extracting opinion expressions from text is usually formulated as a token-level sequence labeling task tackled using Conditional Ran- dom Fields (CRFs). CRFs, however, do not readily model potentially useful segment-level information like syntactic constituent struc- ture. Thus, we propose a semi-CRF-based ap- proach to the task that can perform sequence labeling at the segment level. We extend the original semi-CRF model (Sarawagi and Co- hen, 2004) to allow the modeling of arbitrar- ily long expressions while accounting for their likely syntactic structure when modeling seg- ment boundaries. We evaluate performance on two opinion extraction tasks, and, in contrast to previous sequence labeling approaches to the task, explore the usefulness of segment- level syntactic parse features. Expe...