SemLinker, a Modular and Open Source Framework for Named Entity Discovery and Linking

Marie-Jean Meurs, Hayda Almeida, Ludovic Jean-Louis, 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.
Anthology ID:
L16-1085
Volume:
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
Month:
May
Year:
2016
Address:
Portorož, Slovenia
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Sara Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
536–540
Language:
URL:
https://aclanthology.org/L16-1085
DOI:
Bibkey:
Cite (ACL):
Marie-Jean Meurs, Hayda Almeida, Ludovic Jean-Louis, and Eric Charton. 2016. SemLinker, a Modular and Open Source Framework for Named Entity Discovery and Linking. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 536–540, Portorož, Slovenia. European Language Resources Association (ELRA).
Cite (Informal):
SemLinker, a Modular and Open Source Framework for Named Entity Discovery and Linking (Meurs et al., LREC 2016)
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PDF:
https://aclanthology.org/L16-1085.pdf