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Personal Attributes Extraction in Chinese Text Based on Distant-Supervision and LSTM

  • Wenxi Yao
  • Jin Liu
  • Zehuan Cai
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 474)

Abstract

In this paper, we proposed a distant-supervision approach to solve the problem of insufficient training corpus for extracting attribute from the unstructured text, by using the wiki infobox information to tag the Wikipedia text to get the training corpus. We consider the extract attribute as the sequence annotation question and use the wiki personal text as the training corpus. The clp-2014 task4 is used as the test corpus to test. The experiment result show that this method can enhance the quality of the attribute extraction.

Keywords

Deep learning Entity attribute extraction LSTM  Sequence padding NLP Distant-supervised 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.College of Information EngineeringShanghai Maritime UniversityShanghaiChina

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