Automatic term list generation for entity tagging | Zendy

Ted Sandler | Zendy; Andrew I. Schein | Zendy; Lyle Ungar | Zendy

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Automatic term list generation for entity tagging

Author(s) -

Ted Sandler,

Andrew I. Schein,

Lyle Ungar

Publication year - 2005

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/bti733

Subject(s) - computer science , parsing , complement (music) , cluster analysis , term (time) , natural language processing , precision and recall , information retrieval , artificial intelligence , code (set theory) , programming language , biochemistry , chemistry , physics , set (abstract data type) , quantum mechanics , complementation , gene , phenotype

Many entity taggers and information extraction systems make use of lists of terms of entities such as people, places, genes or chemicals. These lists have traditionally been constructed manually. We show that distributional clustering methods which group words based on the contexts that they appear in, including neighboring words and syntactic relations extracted using a shallow parser, can be used to aid in the construction of term lists.

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