Journal article

Relation extraction using distant supervision: a survey

    2018
Published in:
  • ACM Comput. Surv.. - 2018, vol. 51, no. 5, p. 106:1–106:35
English Relation extraction is a subtask of information extraction where semantic relationships are extracted from natural language text and then classified. In essence, it allows us to acquire structured knowledge from unstructured text. In this article, we present a survey of relation extraction methods that leverage pre-existing structured or semi- structured data to guide the extraction process. We introduce a taxonomy of existing methods and describe distant supervision approaches in detail. We describe, in addition, the evaluation methodologies and the datasets commonly used for quality assessment. Finally, we give a high-level outlook on the field, highlighting open problems as well as the most promising research directions.
Faculty
Faculté des sciences et de médecine
Department
Département d'Informatique
Language
  • English
Classification
Information, communication and media sciences
License
License undefined
Identifiers
Persistent URL
https://folia.unifr.ch/unifr/documents/307719
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