Indirectly Named Entity Recognition
| Autor: | Kauffmann, Alexis, Rey, François-Claude, Atanassova, Iana, Gaudinat, Arnaud, Greenfield, Peter, Madinier, Hélène, Cardey, Sylviane |
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| Přispěvatelé: | Haute Ecole de Gestion de Genève (HEG), Centre de recherches interdisciplinaires et transculturelles - UFC (EA 3224) (CRIT), Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC), Institut Universitaire de France (IUF), Ministère de l'Education nationale, de l’Enseignement supérieur et de la Recherche (M.E.N.E.S.R.), This research has been funded by the FEDER (Fonds européen de développement régional)., Centre de recherches interdisciplinaires et transculturelles - UFC (UR 3224) (CRIT) |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Multiword expressions
multiword expressions Information extraction Text mining named entities [SHS.INFO]Humanities and Social Sciences/Library and information sciences named entity recognition Text processing Indirectly named entities Named entities 02 engineering and technology text mining 16. Peace & justice Named entity recognition [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing indirectly named entities 020204 information systems [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR] 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing [INFO]Computer Science [cs] information extraction text processing [SHS.LANGUE]Humanities and Social Sciences/Linguistics |
| Zdroj: | Journal of Computer-Assisted Linguistic Research (JCLR) Journal of Computer-Assisted Linguistic Research (JCLR), Universitat Politècnica de València, 2021, 5 (1), pp.27-46. ⟨10.4995/JCLR.2021.15922⟩ RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia instname |
| ISSN: | 2530-9455 |
| DOI: | 10.4995/JCLR.2021.15922⟩ |
| Popis: | [EN] 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. This research has been funded by the FEDER (Fonds européen de développement régional) and selected by the French-Swiss programme Interreg V. We would like to thank Claire Wuillemin for her preliminary work in the DecRIPT project about the State-of-the-Art in NER and SER in 2020. We would also like to thank for their advice Gilles Falquet, Luka Nerima, Eric Wehrli and Jean-Philippe Goldman at the University of Geneva. |
| Databáze: | OpenAIRE |
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