Process / pipeline

Semantic Role Labeling (SRL)

Semantic role labeling, introduced by Gildea and Jurafsky in 2002, is a natural-language-processing task that assigns semantic roles — who did what to whom, where, when, and how — to the components around a verb (predicate) in a sentence. It turns plain text into structured predicate-argument representations and is a foundational tool for event extraction.

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Sources

  1. Gildea, D. & Jurafsky, D. (2002). Automatic Labeling of Semantic Roles. Computational Linguistics, 28(3), 245-288. DOI: 10.1162/089120102760275983
  2. Shi, P. & Lin, J. (2019). Simple BERT Models for Relation Extraction and Semantic Role Labeling. arXiv:1904.05255. link

Related methods

Referenced by

ScholarGateSemantic Role Labeling (Semantic Role Labeling (SRL)). Retrieved 2026-06-04 from https://scholargate.app/en/text-mining/semantic-role-labeling