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arXiv · 2011.00105

Learning Structured Representations of Entity Names using Active Learning and Weak Supervision

Kun Qian·Poornima Chozhiyath Raman·Yunyao Li·Lucian Popa
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Abstract

Structured representations of entity names are useful for many entity-related tasks such as entity normalization and variant generation. Learning the implicit structured representations of entity names without context and external knowledge is particularly challenging. In this paper, we present a novel learning framework that combines active learning and weak supervision to solve this problem. Our experimental evaluation show that this framework enables the learning of high-quality models from merely a dozen or so labeled examples.

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Kun Qian, Poornima Chozhiyath Raman, Yunyao Li, Lucian Popa. 2020-10-30. Learning Structured Representations of Entity Names using Active Learning and Weak Supervision. https://arxiv.org/abs/2011.00105

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