Linked Data for Information Extraction Challenge 2014: Tasks and Results

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Provided by: RWTH Aachen University
Topic: Data Management
Format: PDF
For making the web of linked data grow, information extraction methods are a good alternative to manual dataset curation, since there is an abundance of semi-structured and unstructured information which can be harvested that way. At the same time, existing linked data sets can be used for training and evaluating such information extraction systems. In this paper, the authors introduce the linked data for Information extraction challenge 2014. Using the example of person data in Microformats, they show how training and testing data can be curated at large scale.
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