Relation extraction using distant supervision: a survey
- Smirnova, Alisa eXascale Infolab, University of Fribourg, Switzerland
- Cudré-Mauroux, Philippe eXascale Infolab, University of Fribourg, Switzerland
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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
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- English
- Classification
- Information, communication and media sciences
- License
- License undefined
- Identifiers
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- RERO DOC 324377
- DOI 10.1145/3241741
- Persistent URL
- https://folia.unifr.ch/unifr/documents/307719
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