Distilling Hypernymy Relations from Language Models: On the Effectiveness of Zero-Shot Taxonomy Induction

Devansh Jain; Luis Espinosa Anke

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arXiv · 2202.04876

Distilling Hypernymy Relations from Language Models: On the Effectiveness of Zero-Shot Taxonomy Induction

Devansh Jain·Luis Espinosa Anke

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Abstract

In this paper, we analyze zero-shot taxonomy learning methods which are based on distilling knowledge from language models via prompting and sentence scoring. We show that, despite their simplicity, these methods outperform some supervised strategies and are competitive with the current state-of-the-art under adequate conditions. We also show that statistical and linguistic properties of prompts dictate downstream performance.

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Devansh Jain, Luis Espinosa Anke. 2022-02-10. Distilling Hypernymy Relations from Language Models: On the Effectiveness of Zero-Shot Taxonomy Induction. https://arxiv.org/abs/2202.04876

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