Mixup Based Cross-Consistency Training for Named Entity Recognition
Named Entity Recognition (NER) is at the core of natural language understanding. The quality and amount of datasets determine the performance of deep-learning-based NER models. As datasets for NER require token-level or word-level labels to be assigned, annotating the datasets is expensive and time...
Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-11-01
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Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/12/21/11084 |