Indirectly Named Entity Recognition


  • Alexis Kauffmann HES-SO/HEG Genève
  • François-Claude Rey CRIT, University of Bourgogne - Franche-Comté
  • Iana Atanassova CRIT, University of Bourgogne - Franche-Comté ; Institut Universitaire de France (IUF)
  • Arnaud Gaudinat HES-SO/HEG Genève
  • Peter Greenfield CRIT, University of Bourgogne - Franche-Comté
  • Hélène Madinier HES-SO/HEG Genève
  • Sylviane Cardey CRIT, University of Bourgogne - Franche-Comté; Institut Universitaire de France (IUF)



named entities, indirectly named entities, information extraction, named entity recognition, multiword expressions, text processing, text mining


We define here indirectly named entities, as a term to denote multiword expressions referring to known named entities by means of periphrasis.  While named entity recognition is a classical task in natural language processing, little attention has been paid to indirectly named entities and their treatment. In this paper, we try to address this gap, describing issues related to the detection and understanding of indirectly named entities in texts. We introduce a proof of concept for retrieving both lexicalised and non-lexicalised indirectly named entities in French texts. We also show example cases where this proof of concept is applied, and discuss future perspectives. We have initiated the creation of a first lexicon of 712 indirectly named entity entries that is available for future research.


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