Wu and Weld ACL 2010

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Wu, F. and Weld, D. S. 2010. Open information extraction using Wikipedia. In Proceedings of the 48th Annual Meeting of the Association For Computational Linguistics (Uppsala, Sweden, July 11 - 16, 2010). ACL Workshops. Association for Computational Linguistics, Morristown, NJ, 118-127.

Online version

ACM Digital Library


This is a latest paper that addressed the Open Information Extraction problem. Authors proposed an extraction system, WOE. First training data was extracted from Wikipedia using KYLIN (Wu_and_Weld_CIKM_2007), and then it was processed to train an unlexicalized extractor as TEXTRUNNER Banko_et_al_IJCAI_2007. There are many similarities between WOE and the other two systems.

There are three components in the system:

  1. Processor
    • Wikipedia pages are parsed by OpenNLP tools and Standford parser.
    • Redirection and backward links are used to construct the synonym sets for entities.
  2. Matcher
    • For each attribute-value pairs (relations), matcher heuristically look for a reference sentence in the article for it. DBpedia was used for the clean set of infobox.
  3. Extractor
    • First option was to train a classifier to decide if the shortest dependency path between two NPs is a relation. Second option was to train a CRF as in TEXTRUNNER to tag if the words between two NPs are part of a relation.

Three corpus was used in evaluation: 300 random sentences from Penn Treebank WSJ, Wikipedia, and Web pages.

Related papers

More details of KYLIN can be found in Wu_and_Weld_CIKM_2007 in the task of completing infoboxs in Wikipedia pages. TEXTRUNNER was described in Banko_et_al_IJCAI_2007.