Paper: Named Entity Recognition with Bilingual Constraints

ACL ID N13-1006
Title Named Entity Recognition with Bilingual Constraints
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2013

Different languages contain complementary cues about entities, which can be used to im- prove Named Entity Recognition (NER) sys- tems. We propose a method that formu- lates the problem of exploring such signals on unannotated bilingual text as a simple Inte- ger Linear Program, which encourages entity tags to agree via bilingual constraints. Bilin- gual NER experiments on the large OntoNotes 4.0 Chinese-English corpus show that the pro- posed method can improve strong baselines for both Chinese and English. In particular, Chinese performance improves by over 5% absolute F1 score. We can then annotate a large amount of bilingual text (80k sentence pairs) using our method, and add it as up- training data to the original monolingual NER training corpus. The Chinese model retrained on this ne...