Paper: Dynamic Knowledge-Base Alignment for Coreference Resolution

ACL ID W13-3517
Title Dynamic Knowledge-Base Alignment for Coreference Resolution
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2013

Coreference resolution systems can benefit greatly from inclusion of global context, and a number of recent approaches have demonstrated improvements when precom- puting an alignment to external knowledge sources. However, since alignment itself is a challenging task and is often noisy, ex- isting systems either align conservatively, resulting in very few links, or combine the attributes of multiple candidates, leading to a conflation of entities. Our approach instead performs joint inference between within-document coreference and entity linking, maintaining ranked lists of candi- date entities that are dynamically merged and reranked during inference. Further, we incorporate a large set of surface string vari- ations for each entity by using anchor texts from the web that link to the ent...