Classification Attention for Chinese NER
The character-based model, such as BERT, has achieved remarkable success in Chinese named entity recognition (NER). However, such model would likely miss the overall information of the entity words. In this paper, we propose to combine priori entity information with BERT. Instead of relying on additional lexicons or pre-trained word embeddings, our model has generated entity classification embeddings directly on the pre-trained BERT, having the merit of increasing model practicability and avoiding OOV problem. Experiments show that our model has achieved state-of-the-art results on 3 Chinese NER datasets.
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Tasks
Chinese Named Entity RecognitionClassificationnamed-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)NERWord EmbeddingsSimilar Papers 제목 키워드 기반
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