Paper: Analysis And Repair Of Name Tagger Errors

ACL ID P06-2055
Title Analysis And Repair Of Name Tagger Errors
Venue Annual Meeting of the Association of Computational Linguistics
Session Poster Session
Year 2006

Name tagging is a critical early stage in many natural language processing pipe- lines. In this paper we analyze the types of errors produced by a tagger, distin- guishing name classification and various types of name identification errors. We present a joint inference model to im- prove Chinese name tagging by incorpo- rating feedback from subsequent stages in an information extraction pipeline: name structure parsing, cross-document coreference, semantic relation extraction and event extraction. We show through examples and performance measurement how different stages can correct different types of errors. The resulting accuracy approaches that of individual human an- notators.