PTST-UoM at SemEval-2021 Task 10: Parsimonious Transfer for Sequence Tagging
2021-08-01SEMEVALUnverified0· sign in to hype
Kemal Kurniawan, Lea Frermann, Philip Schulz, Trevor Cohn
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This paper describes PTST, a source-free unsupervised domain adaptation technique for sequence tagging, and its application to the SemEval-2021 Task 10 on time expression recognition. PTST is an extension of the cross-lingual parsimonious parser transfer framework, which uses high-probability predictions of the source model as a supervision signal in self-training. We extend the framework to a sequence prediction setting, and demonstrate its applicability to unsupervised domain adaptation. PTST achieves F1 score of 79.6\% on the official test set, with the precision of 90.1\%, the highest out of 14 submissions.