Are Expert-Level Language Models Expert-Level Annotators?

ACL ARR 2024 June Submission5827 Authors

16 Jun 2024 (modified: 02 Jul 2024)ACL ARR 2024 June SubmissionEveryoneRevisionsBibTeXCC BY 4.0
Abstract: Data annotation refers to the labeling or tagging of textual data with relevant information. A large body of works have reported positive results on leveraging LLMs as an alternative to human annotators. However, existing studies focus on classic NLP tasks, and the extent to which LLMs as data annotators perform in domains requiring expert knowledge remains underexplored. In this work, we investigate comprehensive approaches across three highly specialized domains and discuss practical suggestions from a cost-effectiveness perspective. To the best of our knowledge, we present the first systematic evaluation of LLMs as expert-level data annotators.
Paper Type: Short
Research Area: NLP Applications
Research Area Keywords: LLMs, LLM as Annotators
Languages Studied: English
Submission Number: 5827
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