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Enhancing online knowledge graph population with semantic knowledge

Author
Fernández, D.; Rimmek, J.; Espadaler, J.; Garolera, B.; Barja, A.; Codina, M.; Sastre, M.; Giro, X.; Riveiro, J. C.; Bou, E.
Type of activity
Book chapter
Book
The Semantic Web – ISWC: 2020 19th International Semantic Web Conference: Athens, Greece: November 2–6, 2020: Proceedings, Part I
First page
183
Last page
200
Publisher
Springer
Date of publication
2020-11-01
ISBN
978-3-030-62419-4
DOI
10.1007/978-3-030-62419-4
Repository
http://hdl.handle.net/2117/332082 Open in new window
URL
https://link.springer.com/book/10.1007/978-3-030-62419-4 Open in new window
Abstract
Knowledge Graphs (KG) are becoming essential to organize, represent and store the world’s knowledge, but they still rely heavily on humanly-curated structured data. Information Extraction (IE) tasks, like disambiguating entities and relations from unstructured text, are key to automate KG population. However, Natural Language Processing (NLP) methods alone can not guarantee the validity of the facts extracted and may introduce erroneous information into the KG. This work presents an end-to-end...
Citation
Fernàndez, D. [et al.]. Enhancing online knowledge graph population with semantic knowledge. A: "The Semantic Web – ISWC: 2020 19th International Semantic Web Conference: Athens, Greece: November 2–6, 2020: Proceedings, Part I". Berlín: Springer, 2020, p. 183-200.
Keywords
Data validation, Knowledge graph, Relation extraction
Group of research
GPI - Image and Video Processing Group
Universitat Politècnica de Catalunya

Participants

  • Fernández Cañellas, Dèlia  (author)
  • Rimmek, Joan Marco  (author)
  • Espadaler Rodés, Joan  (author)
  • Garolera Huguet, Blai  (author)
  • Barja Romero, Adrià  (author)
  • Codina, Marc  (author)
  • Sastre Rienitz, Marc  (author)
  • Giro Nieto, Xavier  (author)
  • Riveiro, Juan Carlos  (author)
  • Bou Balust, Elisenda  (author)

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