Summary of the paper

Title ELMD: An Automatically Generated Entity Linking Gold Standard Dataset in the Music Domain
Authors Sergio Oramas, Luis Espinosa Anke, Mohamed Sordo, Horacio Saggion and Xavier Serra
Abstract In this paper we present a gold standard dataset for Entity Linking (EL) in the Music Domain. It contains thousands of musical named entities such as Artist, Song or Record Label, which have been automatically annotated on a set of artist biographies coming from the Music website and social network Last.fm. The annotation process relies on the analysis of the hyperlinks present in the source texts and in a voting-based algorithm for EL, which considers, for each entity mention in text, the degree of agreement across three state-of-the-art EL systems. Manual evaluation shows that EL Precision is at least 94%, and due to its tunable nature, it is possible to derive annotations favouring higher Precision or Recall, at will. We make available the annotated dataset along with evaluation data and the code.
Topics Corpus (Creation, Annotation, etc.), Named Entity Recognition, Semantics
Full paper ELMD: An Automatically Generated Entity Linking Gold Standard Dataset in the Music Domain
Bibtex @InProceedings{ORAMAS16.501,
  author = {Sergio Oramas and Luis Espinosa Anke and Mohamed Sordo and Horacio Saggion and Xavier Serra},
  title = {ELMD: An Automatically Generated Entity Linking Gold Standard Dataset in the Music Domain},
  booktitle = {Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)},
  year = {2016},
  month = {may},
  date = {23-28},
  location = {Portoro┼ż, Slovenia},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Sara Goggi and Marko Grobelnik and Bente Maegaard and Joseph Mariani and Helene Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  address = {Paris, France},
  isbn = {978-2-9517408-9-1},
  language = {english}
 }
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