On Jointly Recognizing and Aligning Bilingual Named Entities
Yufeng Chen, Chengqing Zong, Keh‐Yih Su · 2010
We observe that (1) how a given named en-tity (NE) is translated (i.e., either semanti-cally or phonetically) depends greatly on its associated entity type, and (2) entities within an aligned pair should share the same type. Also, (3) those initially detected NEs are an-chors, whose information should be used to give certainty scores when selecting candi-dates. From this basis, an integrated model is thus proposed in this paper to jointly identify and align bilingual named entities between Chinese and English. It adopts a new map-ping type ratio feature (which is the propor-tion of NE internal tokens that are semanti-cally translated), enforces an entity type con-sistency constraint, and utilizes additional monolingual candidate certainty factors (based on those NE anchors). The experi-ments show that this novel approach has sub-stantially raised the type-sensitive F-score of identified NE-pairs from 68.4 % to 81.7% (42.1 % F-score imperfection reduction) in our Chinese-English NE alignment task. 1