Papers with name entity recognition

2 papers
Trigger Word Detection and Thematic Role Identification via BERT and Multitask Learning (D19-57)

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Challenge: Using natural language processing to discover and mine drug-related knowledge from text has been a hot topic in recent years.
Approach: They propose to use a pre-trained biomedical language representation model to extract mutation-disease knowledge from PubMed.
Outcome: The proposed approaches achieve 0.60 (ranks 1) and 0.25 (rank 2) on task 1 and task 2 respectively in terms of F1 metric.
Similarity Based Auxiliary Classifier for Named Entity Recognition (D19-1)

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Challenge: Named entity recognition (NER) tasks are a fundamental challenge for name recognition tasks that aim to reduce the boundary error when entities become longer.
Approach: They propose a similarity based auxiliary classifier which can distinguish entity words from non-entity words by using vectors to indicate tags.
Outcome: Empirical results show that the proposed classifier can perform better than baseline approaches.

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