Promoting Named Entity Recognition with External Discriminator

In this paper, we propose an NER promotion method formed as an external discriminator. It learns the patterns about the contextual entity usages from the extensive web data and thus it can check whether the recognized entity by an NER model is correct. Different with the current popular methods on introducing the entity knowledge by gazetteers or labeled data, it can be used as the additional part to work with any NER method for promoting its performance. We adopt three widely adopted datasets for the empirical studies and the results show that our method significantly improves the NER performance. Besides, by using only a small proportion of labeled data, our method achieves a comparable performance against other models using the whole labeled data.