Chinese Named Entity Abbreviation Generation Using First-Order Logic

Normalizing named entity abbreviations to their standard forms is an important preprocessing task for question answering, entity retrieval, event detection, microblog processing, and many other applications. Along with the quick expansion of microblogs, this task has received more and more attentions in recent years. In this paper, we propose a novel entity abbreviation generation method using first-order logic to model long distance constraints. In order to reduce the human effort of manual annotating corpus, we also introduce an automatically training data construction method with simple strategies. Experimental results demonstrate that the proposed method achieves better performance than state-of-the-art approaches.