[Adapt] [Semina]Improving Information Extraction by Acquiring External Evidence with Reinforcement Learning
邢俊劼
jjxing at sjtu.edu.cn
Wed Apr 26 09:10:50 CST 2017
Hi Adapters,
This afternoon I’ll give a talk about an interesting approach to information extraction.
When facing an IE task, a common issue is that “ambiguous” expression occurs. For example, when extracting number of people from “A couple and their four children had a good vacation”, the extractor may return an incorrect answer because “couple” stands for two people. Even a large annotated model may not cover such cases.
The paper gives an approach to solve the problem by using external information from web and reconcile to a more accurate output, not enlarging the label process or adding ambiguous words handling.
Models in this paper are a basic extractor based on CRF and a simple reinforcement learning model. The overall process lays on a markov decision process.
See you this afternoon!
Best wishes,
Gavin
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