@prefix owl: <http://www.w3.org/2002/07/owl#> .
@prefix skos: <http://www.w3.org/2004/02/skos/core#> .
@prefix dc: <http://purl.org/dc/terms/> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .
@prefix inist: <http://www.inist.fr/Ontology#> .

<http://data.loterre.fr/ark:/67375/8LP> a owl:Ontology, skos:ConceptScheme .
<http://data.loterre.fr/ark:/67375/8LP-T5LX5T16-C>
  skos:prefLabel "question answering system"@en, "système de questions réponses"@fr ;
  a skos:Concept ;
  skos:narrower <http://data.loterre.fr/ark:/67375/8LP-ZWNX93XW-B> .

<http://data.loterre.fr/ark:/67375/8LP-ZWNX93XW-B>
  skos:hiddenLabel "Machine reading comprehension"@en, "Lecture automatique de documents"@fr ;
  skos:altLabel "reading comprehension"@en, "MRC"@en, "extractive question answering"@en, "question-réponse"@fr, "compréhension de texte"@fr ;
  dc:modified "2024-06-26T09:08:42"^^xsd:dateTime ;
  skos:example "On top of this feature extractor we add a linear layer for extractive question answers whose output dimension is two. (Yin, Wang, Dong & Ling, 2024)"@en, "Machine reading comprehension has been increasingly studied in the NLP area which aims to read a given passage and then answer questions correctly. (Yeh & Chen, 2019)"@en, "MRC is the ability to answer the question based on the input paragraph of the text. (Galitsky, Ilvovsky & Goncharova, 2021)"@en, "Also MRC failed to match the question with the sentence \"However clinicians are not always able to find out which germ caused someone to get sick with pneumonia.\". (Galitsky, Ilvovsky & Goncharova, 2021)"@en ;
  skos:definition "A task that requires machines to read a text, comprehend given passages and answer questions related to the text. (Cui et al., ExpMRC: explainability evaluation for machine reading comprehension, in Heliyon, 2022)"@en, "Cas particulier de la tâche de question/réponse où une machine répond à des questions portant sur un document écrit particulier, chaque réponse se présentant sous la forme d’un passage du document. (D'après Bechet et al., CALOR-QUEST : un corpus d’entraînement et d’évaluation pour la compréhension automatique de textes, TALN, 2019)"@fr ;
  inist:definitionalContext "Machine reading comprehension (MRC) reflects the ability to read and understand an unstructured text and answer questions regarding it. (Galitsky, Ilvovsky & Goncharova, 2021)"@en, "Extractive question answering (extractive QA) aims to provide answer spans extracted from the context to answer questions. (Nie, Huang, Chi & Mao, 2022)"@en, "Extractive question answering is a common task in NLP where the goal is to select a contiguous span a from a given text T that answers a question Q. (Ram, Kirstain, Berant, Globerson & Levy, 2021)"@en, "Machine reading comprehension aims to assess the ability to comprehend natural language and answer questions from a given document or passage. (Zheng, Huang & Sun, 2019)"@en, "Extractive Question Answering (Extractive-QA) is a common and widely used task where a model is tasked with locating and reproducing an answer to a question posed directly with regard to a source text. (Cohen, Merhav-Fine, Goldberg & Tsarfaty, 2023)"@en ;
  a skos:Concept ;
  skos:exactMatch <https://www.wikidata.org/wiki/Q124149560> ;
  skos:broader <http://data.loterre.fr/ark:/67375/8LP-T5LX5T16-C> ;
  skos:prefLabel "lecture automatique de documents"@fr, "machine reading comprehension"@en ;
  skos:inScheme <http://data.loterre.fr/ark:/67375/8LP> .