Paper: A Statistical Model For Multilingual Entity Detection And Tracking

ACL ID N04-1001
Title A Statistical Model For Multilingual Entity Detection And Tracking
Venue Human Language Technologies
Session Main Conference
Year 2004
Authors

Entity detection and tracking is a relatively new addition to the repertoire of natural language tasks. In this paper, we present a statistical language-independent framework for identify- ing and tracking named, nominal and pronom- inal references to entities within unrestricted text documents, and chaining them into clusters corresponding to each logical entity present in the text. Both the mention detection model and the novel entity tracking model can use arbitrary feature types, being able to integrate a wide array of lexical, syntactic and seman- tic features. In addition, the mention detec- tion model crucially uses feature streams de- rived from different named entity classifiers. The proposed framework is evaluated with sev- eral experiments run in Arabic, Chinese and English text...