LREC 2006 - Proceedings sorted by papers

Title	Identifying Named Entities in Text Databases from the Natural History Domain
Authors	C. Sporleder, M. Erp, T. Porcelijn, A. Bosch, P. Arntzen
Abstract	In this paper, we investigate whether it is possible to bootstrap a named entity tagger for textual databases by exploiting the database structure to automatically generate domain and database-specific gazetteer lists. We compare three tagging strategies: (i) using the extracted gazetteers in a look-up tagger, (ii) using the gazetteers to automatically extract training data to train a database-specific tagger, and (iii) using a generic named entity tagger. Our results suggest that automatically built gazetteers in combination with a look-up tagger lead to a relatively good performance and that generic taggers do not perform particularly well on this type of data.
Keywords	Named-Entity TaggingText DatabasesMachine Learning
Full paper	Identifying Named Entities in Text Databases from the Natural History Domain

Title

Identifying Named Entities in Text Databases from the Natural History Domain

Authors

C. Sporleder, M. Erp, T. Porcelijn, A. Bosch, P. Arntzen

Abstract

In this paper, we investigate whether it is possible to bootstrap a named entity tagger for textual databases by exploiting the database structure to automatically generate domain and database-specific gazetteer lists. We compare three tagging strategies: (i) using the extracted gazetteers in a look-up tagger, (ii) using the gazetteers to automatically extract training data to train a database-specific tagger, and (iii) using a generic named entity tagger. Our results suggest that automatically built gazetteers in combination with a look-up tagger lead to a relatively good performance and that generic taggers do not perform particularly well on this type of data.

Keywords

Named-Entity TaggingText DatabasesMachine Learning

Full paper

Identifying Named Entities in Text Databases from the Natural History Domain