Paper: Towards Robust Unsupervised Personal Name Disambiguation

ACL ID D07-1020
Title Towards Robust Unsupervised Personal Name Disambiguation
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2007
Authors

The increasing use of large open-domain document sources is exacerbating the problem of ambiguity in named entities. This paper explores the use of a range of syntactic and semantic features in unsu- pervised clustering of documents that re- sult from ad hoc queries containing names. From these experiments, we find that the use of robust syntactic and semantic fea- tures can significantly improve the state of the art for disambiguation performance for personal names for both Chinese and Eng- lish.