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Vocabulary of natural language processing

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Concept information

Terme préférentiel

named entity recognition  

Définition

  • A subtask of information extraction that seeks to locate and classify named entities in text into pre-defined categories such as the names of persons, organizations, locations, expressions of times, quantities, monetary values, percentages, etc. (Loterre)

Concept générique

Synonyme(s)

  • entity chunking
  • entity extraction
  • entity identification
  • entity recognition
  • named entities recognition
  • named entity extraction
  • NER

Contexte(s) définitoire(s)

  • Named Entity Recognition (NER) (also known as Entity Recognition Entity Chunking and Entity Extraction) is a subtask of Information Extraction that aims to locate and classify named entities in text into predefined categories such as people organizations locations etc. (Zhang, Wang & Zhang, 2023)

Exemple

  • It applies filtering techniques based on intuitive rules as well as the expected answer classes with named-entities recognition defined by regular expressions and a fixed list for some special cases. (Pizzato & Mollá, 2008)
  • Named Entity Extraction is a mature task in the NLP field that has yielded numerous services gaining popularity in the Semantic Web community for extracting knowledge from web documents. (Rizzo & Troncy, 2012)
  • Named Entity Recognition (NER) is one of the most fundamental tasks in natural language processing. (Zhang, Qiao, Zhao, Tao & Yang, 2023)
  • Named entity recognition (NER) locates units of information such as names of organizations persons and locations and numeric expressions from unstructured text. (Kayal, Afzal, Tsatsaronis, Katrenko, Coupet, Doornenbal & Gregory, 2017)
  • We introduce a named-entity extraction method to recognize named entities from embedded images in articles eliminating the overhead in manually creating a list of named entities that will appear in the articles. (Zhang, Gu & Plummer, 2023)

Traductions

URI

http://data.loterre.fr/ark:/67375/8LP-C3FMJCQM-G

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