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ZS4IE: A toolkit for Zero-Shot Information Extraction with simple Verbalizations

2022-03-25 12:02:53
Oscar Sainz, Haoling Qiu, Oier Lopez de Lacalle, Eneko Agirre, Bonan Min
arXiv_CL
         
Abstract

The current workflow for Information Extraction (IE) analysts involves the definition of the entities/relations of interest and a training corpus with annotated examples. In this demonstration we introduce a new workflow where the analyst directly verbalizes the entities/relations, which are then used by a Textual Entailment model to perform zero-shot IE. We present the design and implementation of a toolkit with a user interface, as well as experiments on four IE tasks that show that the system achieves very good performance at zero-shot learning using only 5--15 minutes per type of a user's effort. Our demonstration system is open-sourced at this https URL . A demonstration video is available at this https URL .

Abstract (translated)

URL

https://arxiv.org/abs/2203.13602

PDF

https://arxiv.org/pdf/2203.13602.pdf

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