DSP: Discriminative Soft Prompts for Zero-Shot Entity and Relation Extraction

Bo Lv, Xin Liu, Shaojie Dai, Nayu Liu, Fan Yang, Ping Luo, Yue Yu


Abstract
Prompt-based methods have shown their efficacy in transferring general knowledge within pre-trained language models (PLMs) for low-resource scenarios. Typically, prompt-based methods convert downstream tasks to cloze-style problems and map all labels to verbalizers.However, when applied to zero-shot entity and relation extraction, vanilla prompt-based methods may struggle with the limited coverage of verbalizers to labels and the slow inference speed. In this work, we propose a novel Discriminate Soft Prompts (DSP) approach to take advantage of the prompt-based methods to strengthen the transmission of general knowledge. Specifically, we develop a discriminative prompt method, which reformulates zero-shot tasks into token discrimination tasks without having to construct verbalizers.Furthermore, to improve the inference speed of the prompt-based methods, we design a soft prompt co-reference strategy, which leverages soft prompts to approximately refer to the vector representation of text tokens. The experimental results show that, our model outperforms baselines on two zero-shot entity recognition datasets with higher inference speed, and obtains a 7.5% average relation F1-score improvement over previous state-of-the-art models on Wiki-ZSL and FewRel.
Anthology ID:
2023.findings-acl.339
Volume:
Findings of the Association for Computational Linguistics: ACL 2023
Month:
July
Year:
2023
Address:
Toronto, Canada
Editors:
Anna Rogers, Jordan Boyd-Graber, Naoaki Okazaki
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
5491–5505
Language:
URL:
https://aclanthology.org/2023.findings-acl.339
DOI:
10.18653/v1/2023.findings-acl.339
Bibkey:
Cite (ACL):
Bo Lv, Xin Liu, Shaojie Dai, Nayu Liu, Fan Yang, Ping Luo, and Yue Yu. 2023. DSP: Discriminative Soft Prompts for Zero-Shot Entity and Relation Extraction. In Findings of the Association for Computational Linguistics: ACL 2023, pages 5491–5505, Toronto, Canada. Association for Computational Linguistics.
Cite (Informal):
DSP: Discriminative Soft Prompts for Zero-Shot Entity and Relation Extraction (Lv et al., Findings 2023)
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PDF:
https://aclanthology.org/2023.findings-acl.339.pdf