Automatic Discovery of Named Entity Variants. Association of Computational Linguistics Annual Meeting, Prague-Czech

Identification of transliterated names is a particularly difficult task of Named Entity Recognition (NER), especially in the Chi-nese context. Of all possible variations of transliterated named entities, the difference between PRC and Taiwan is the most preva-lent and most challenging. In this paper, we introduce a novel approach to the automatic extraction of diverging transliterations of foreign named entities by bootstrapping co-occurrence statistics from tagged and seg-mented Chinese corpus. Preliminary experi-ment yields promising results and shows its potential in NLP applications.