Paper: Joint Coreference Resolution and Named-Entity Linking with Multi-Pass Sieves

ACL ID D13-1029
Title Joint Coreference Resolution and Named-Entity Linking with Multi-Pass Sieves
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2013
Authors

Many errors in coreference resolution come from semantic mismatches due to inadequate world knowledge. Errors in named-entity linking (NEL), on the other hand, are of- ten caused by superficial modeling of entity context. This paper demonstrates that these two tasks are complementary. We introduce NECO, a new model for named entity linking and coreference resolution, which solves both problems jointly, reducing the errors made on each. NECO extends the Stanford determinis- tic coreference system by automatically link- ing mentions to Wikipedia and introducing new NEL-informed mention-merging sieves. Linking improves mention-detection and en- ables new semantic attributes to be incorpo- rated from Freebase, while coreference pro- vides better context modeling by propagat- ing named-entity l...