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arXiv · 1610.09914

Named Entity Recognition for Novel Types by Transfer Learning

Lizhen Qu·Gabriela Ferraro·Liyuan Zhou·Weiwei Hou·Timothy Baldwin
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Abstract

In named entity recognition, we often don't have a large in-domain training corpus or a knowledge base with adequate coverage to train a model directly. In this paper, we propose a method where, given training data in a related domain with similar (but not identical) named entity (NE) types and a small amount of in-domain training data, we use transfer learning to learn a domain-specific NE model. That is, the novelty in the task setup is that we assume not just domain mismatch, but also label mismatch.

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Lizhen Qu, Gabriela Ferraro, Liyuan Zhou, Weiwei Hou, Timothy Baldwin. 2016-10-31. Named Entity Recognition for Novel Types by Transfer Learning. https://arxiv.org/abs/1610.09914

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