Paper: Streaming Cross Document Entity Coreference Resolution

ACL ID C10-2121
Title Streaming Cross Document Entity Coreference Resolution
Venue International Conference on Computational Linguistics
Session Poster Session
Year 2010
Authors

Previous research in cross-document en- tity coreference has generally been re- stricted to the offline scenario where the set of documents is provided in advance. As a consequence, the dominant approach is based on greedy agglomerative cluster- ing techniques that utilize pairwise vec- tor comparisons and thus require O(n2) space and time. In this paper we ex- plore identifying coreferent entity men- tions across documents in high-volume streaming text, including methods for uti- lizing orthographic and contextual infor- mation. We test our methods using several corpora to quantitatively measure both the efficacy and scalability of our streaming approach. We show that our approach scales to at least an order of magnitude larger data than previous reported meth- ods.