Paper: Using Corpus-Derived Name Lists For Named Entity Recognition

ACL ID A00-1040
Title Using Corpus-Derived Name Lists For Named Entity Recognition
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2000
Authors

This paper describes experiments to establish the performance of a named entity recognition system which builds categorized lists of names from manu- ally annotated training data. Names in text are then identified using only these lists. This approach does not perform as well as state-of-the-art named en- tity recognition systems. However, we then show that by using simple filtering techniques for improv- ing the automatically acquired lists, substantial per- formance benefits can be achieved, with resulting F- measure scores of 87% on a standard test set. These results provide a baseline against which the con- tribution of more sophisticated supervised learning techniques for NE recognition should be measured.