Papers with BERT-based tagging model

1 papers
Code and Named Entity Recognition in StackOverflow (2020.acl-main)

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Challenge: StackOverflow has 15 million programming related questions written by 8.5 million users . however, there is a lack of fundamental NLP resources and techniques for identifying software-related named entities within natural language sentences.
Approach: They propose a named entity recognition corpus for the computer programming domain with 15,372 sentences annotated with 20 fine-grained entity types.
Outcome: The proposed model improves on 152 million sentences from StackOverflow and achieves 79.10 F-1 score for code and named entity recognition.

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