Knowledge-based extraction of named entities James P. Callan and Teruko Mitamura   View Paper (PDF)   Return to Information retrieval Abstract The usual approach to named-entity detection is to learn extraction rules that rely on linguistic, syntactic, or document format patterns that are consistent across a set of documents. However, when there is no consistency among documents, it may be more effective to learn document-specific extraction rules.This paper presents a knowledge-based approach to learning rules for named-entity extraction. Document-specific extraction rules are created using a generate-and-test paradigm and a database of known named-entities. Experimental results show that this approach is effective on Web documents that are difficult for the usual methods. DiSC'03 © 2003 Association for Computing Machinery