A weakly supervised NER model combines classification pretraining on noisy data with Partial-CRFs and non-entity sampling on clean data, improving F1 across five low-resource languages and a fine-grained food domain.
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Low-Resource Name Tagging Learned with Weakly Labeled Data
A weakly supervised NER model combines classification pretraining on noisy data with Partial-CRFs and non-entity sampling on clean data, improving F1 across five low-resource languages and a fine-grained food domain.