# SemEval-2020 Task 6: Definition extraction from free text with the DEFT corpus

arXiv: https://arxiv.org/abs/2008.13694 · HTML: https://mlsanity.com/paper/2008.13694/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 Aug 2020.

## Built on by (most cited first, 12 of 12)

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- [CuRIAM: Corpus re Interpretation and Metalanguage in U.S. Supreme Court Opinions](https://mlsanity.com/paper/2305.14719/) (2023)
- [Transferring Natural Language Datasets Between Languages Using Large Language Models for Modern Decision Support and Sci-Tech Analytical Systems](https://mlsanity.com/paper/2410.14074/) (2024)
- [Leveraging Large Language Models for Automated Definition Extraction with TaxoMatic A Case Study on Media Bias](https://mlsanity.com/paper/2504.00343/) (2025)
- [3D-EX : A Unified Dataset of Definitions and Dictionary Examples](https://mlsanity.com/paper/2308.03043/) (2023)
- [Defx at SemEval-2020 Task 6: Joint Extraction of Concepts and Relations for Definition Extraction](https://mlsanity.com/paper/2103.17090/) (2021)
- [Envisioning the Next-Gen Document Reader](https://mlsanity.com/paper/2302.07492/) (2023)
- [WIKITIDE: A Wikipedia-Based Timestamped Definition Pairs Dataset](https://mlsanity.com/paper/2308.03582/) (2023)

## Abstract (arXiv)

Research on definition extraction has been conducted for well over a decade, largely with significant constraints on the type of definitions considered. In this work, we present DeftEval, a SemEval shared task in which participants must extract definitions from free text using a term-definition pair corpus that reflects the complex reality of definitions in natural language. Definitions and glosses in free text often appear without explicit indicators, across sentences boundaries, or in an otherwise complex linguistic manner. DeftEval involved 3 distinct subtasks: 1)Sentence classification, 2) sequence labeling, and 3) relation extraction.