Summary of the paper

Title SemLinker, a Modular and Open Source Framework for Named Entity Discovery and Linking
Authors Marie-Jean Meurs, Hayda Almeida, Ludovic Jean-Louis and Eric Charton
Abstract This paper presents SemLinker, an open source system that discovers named entities, connects them to a reference knowledge base, and clusters them semantically. SemLinker relies on several modules that perform surface form generation, mutual disambiguation, entity clustering, and make use of two annotation engines. SemLinker was evaluated in the English Entity Discovery and Linking track of the Text Analysis Conference on Knowledge Base Population, organized by the US National Institute of Standards and Technology. Along with the SemLinker source code, we release our annotation files containing the discovered named entities, their types, and position across processed documents.
Topics Named Entity Recognition, Tools, Systems, Applications, Knowledge Discovery/Representation
Full paper SemLinker, a Modular and Open Source Framework for Named Entity Discovery and Linking
Bibtex @InProceedings{MEURS16.349,
  author = {Marie-Jean Meurs and Hayda Almeida and Ludovic Jean-Louis and Eric Charton},
  title = {SemLinker, a Modular and Open Source Framework for Named Entity Discovery and Linking},
  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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