Papers with soft matching module

1 papers
TriggerNER: Learning with Entity Triggers as Explanations for Named Entity Recognition (2020.acl-main)

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Challenge: Named entity recognition (NER) is a fundamental information extraction task that focuses on extracting entities from a given text and classifying them using pre-defined categories.
Approach: They propose to use “entity triggers” to facilitate label-efficient learning of NER models.
Outcome: The proposed model is significantly more cost-effective than the traditional neural NER frameworks.

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