Developing a Sustainable Platform for Entity Annotation Benchmarks

نویسندگان

  • Michael Röder
  • Ricardo Usbeck
  • Axel-Cyrille Ngonga Ngomo
چکیده

The existing entity annotation systems that drive the extraction of RDF from unstructured data are hard to compare as their evaluation relies on different data sets and measures. We developed GERBIL, an evaluation framework for semantic entity annotation that provides developers, end users and researchers with easy-to-use interfaces for the agile, fine-grained and uniform evaluation of 9 annotation tools on 11 different data sets within 6 different experimental settings on 6 different measures. In this paper, we present the developed interfaces, data flows and data structures. Moreover, we show how GERBIL supports a better reproducibility and archiving of experimental results.

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تاریخ انتشار 2015