Language independent NER using a maximum entropy tagger
| Author(s) : | Stephen Clark James R. Curran, |
| Publisher : | N/A |
| Publication Date : | 2003 |
| ISSN : | N/A |
| Abstract : | Named Entity Recognition (NER) systems need to integrate a wide variety of information for optimal performance. This paper demonstrates that a maximum entropy tagger can effectively encode such information and identify named entities with very high accuracy. The tagger uses features which can be obtained for a variety of languages and works effectively not only for English, but also for other languages such, |