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Unsupervised Pronoun Resolution via Masked Noun-Phrase Prediction

2021-05-26 08:30:18
Ming Shen, Pratyay Banerjee, Chitta Baral
arXiv_CL
             
Abstract

In this work, we propose Masked Noun-Phrase Prediction (MNPP), a pre-training strategy to tackle pronoun resolution in a fully unsupervised setting. Firstly, We evaluate our pre-trained model on various pronoun resolution datasets without any finetuning. Our method outperforms all previous unsupervised methods on all datasets by large margins. Secondly, we proceed to a few-shot setting where we finetune our pre-trained model on WinoGrande-S and XS. Our method outperforms RoBERTa-large baseline with large margins, meanwhile, achieving a higher AUC score after further finetuning on the remaining three official splits of WinoGrande.

Abstract (translated)

URL

https://arxiv.org/abs/2105.12392

PDF

https://arxiv.org/pdf/2105.12392.pdf

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