=Paper=
{{Paper
|id=Vol-1581/paper11
|storemode=property
|title=None
|pdfUrl=https://ceur-ws.org/Vol-1581/paper11.pdf
|volume=Vol-1581
}}
==None==
<pdf width="1500px">https://ceur-ws.org/Vol-1581/paper11.pdf</pdf>
<pre>
   Evaluating Entity Linking: An Analysis of
  Current Benchmark Datasets and a Roadmap
            for Doing a Better Job

Filip Ilievski1 Pablo Mendes2 , Heiko Paulheim3 , Julien Plu4 , Giuseppe Rizzo4 ,
            Felix Tristam5 , Marieke van Erp,1 , and Jörg Waitelonis6
                           1
                             VU University Amsterdam
                              2
                                IBM Research USA
                            3
                              Universtiy of Mannheim
                                  4
                                    EURECOM
                          5
                            CITEC, Bielefeld University
                  6
                    Hasso-Plattner-Institut, Universität Potsdam



      Abstract. Entity linking has become a popular task in both natural
      language processing and semantic web communities. However, we find
      that the benchmark datasets for entity linking tasks do not accurately
      evaluate entity linking systems. In this paper, we aim to chart strengths
      and weaknesses of current benchmark datasets and sketch a roadmap for
      the community to devise better benchmark datasets.
      An extended abstract that followed from this discussion was submitted
      to LREC 2016.

      Keywords: natural language processing, semantic web, entity linking

</pre>