YaLi: a crowdsourcing plug-in for NERD

Authors:
Yafang Wang;Lili Jiang;Johannes Hoffart;Gerhard Weikum
Affiliations:
Max Planck Institute for Informatics, Saarbrüecken, Germany;Max Planck Institute for Informatics, Saarbrüecken, Germany;Max Planck Institute for Informatics, Saarbrüecken, Germany;Max Planck Institute for Informatics, Saarbrüecken, Germany
Venue:
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Year:
2013

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Abstract

We demonstrate the YaLi browser plug-in which discovers named entities in Web pages and provides background knowledge about them. The plug-in is implemented with two purposes. From a user perspective, it enriches the browsing experience with entities, helping users with their information needs. From the research perspective, we aim to improve the methods that are used for named entity recognition and disambiguation (NERD) by leveraging the plug-in as an implicit crowdsourcing platform. YaLi tracks the system's errors and the users' corrections, and also gathers implicit training data for improving NERD accuracy.