Paper: Incremental Joint Extraction of Entity Mentions and Relations

ACL ID P14-1038
Title Incremental Joint Extraction of Entity Mentions and Relations
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2014
Authors

We present an incremental joint frame- work to simultaneously extract entity men- tions and relations using structured per- ceptron with efficient beam-search. A segment-based decoder based on the idea of semi-Markov chain is adopted to the new framework as opposed to traditional token-based tagging. In addition, by virtue of the inexact search, we developed a num- ber of new and effective global features as soft constraints to capture the inter- dependency among entity mentions and relations. Experiments on Automatic Con- tent Extraction (ACE) 1 corpora demon- strate that our joint model significantly outperforms a strong pipelined baseline, which attains better performance than the best-reported end-to-end system.