PTST-UoM at SemEval-2021 Task 10: Parsimonious Transfer for Sequence Tagging

Abstract

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 (Kurniawan et al., 2021), 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.