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

• URL: http://arxiv.org/abs/2011.00105v1
• Date: Fri, 30 Oct 2020 21:01:22 GMT
• Title: Learning Structured Representations of Entity Names using Active Learning and Weak Supervision
• Authors: Kun Qian, Poornima Chozhiyath Raman, Yunyao Li, Lucian Popa
• Abstract summary: 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.
• Score: 19.780301040411008
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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