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arXiv · 2005.00087

Revisiting Unsupervised Relation Extraction

Thy Thy Tran·Phong Le·Sophia Ananiadou
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Abstract

Unsupervised relation extraction (URE) extracts relations between named entities from raw text without manually-labelled data and existing knowledge bases (KBs). URE methods can be categorised into generative and discriminative approaches, which rely either on hand-crafted features or surface form. However, we demonstrate that by using only named entities to induce relation types, we can outperform existing methods on two popular datasets. We conduct a comparison and evaluation of our findings with other URE techniques, to ascertain the important features in URE. We conclude that entity types provide a strong inductive bias for URE.

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Thy Thy Tran, Phong Le, Sophia Ananiadou. 2020-04-30. Revisiting Unsupervised Relation Extraction. https://arxiv.org/abs/2005.00087

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