BibSonomy ::  publication ::

The development of natural language proccessing NLP systems that perform machine translation MT and information retrieval IR has highlighted the need for the automatic recognition of proper names. While various name recognizers have been developed, they suffer from being too limited; some only recognize one name class, and all are language specific. This work develops an approach to multilingual name recognition that allows a system optimized for one language to be ported to another with little additional effort and resources. An initial core set of linguistic features, useful for name recognition in most languages, is identified. When porting to a new language, these features need to be converted partly by hand, partly by on-line lists, after which point machine learning ML techniques build decision trees that map features to name classes. A system initially optimized for English has been successfully ported to Spanish and Japanese. Only a few days of human effort for each new language results in performance levels comparable to that of the best current English systems.