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Symlink: A New Dataset for Scientific Symbol-Description Linking

2022/04/26 by Viet Dac Lai, Amir Pouran Ben Veyseh, Lai, Viet Dac +5
Arts and Humanities · Computer Science · #Computation and Language (cs.CL) #Digital Humanities and Scholarship #FOS: Computer and information sciences #Mathematics, Computing, and Information Processing #Natural Language Processing Techniques

paper · pdf · doi:10.48550/arxiv.2204.12070

openalex publication_date 2022/04/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Mathematical symbols and descriptions appear in various forms across document section boundaries without explicit markup. In this paper, we present a new large-scale dataset that emphasizes extracting symbols and descriptions in scientific documents. Symlink annotates scientific papers of 5 different domains (i.e., computer science, biology, physics, mathematics, and economics). Our experiments on Symlink demonstrate the challenges of the symbol-description linking task for existing models and call for further research effort in this area. We will publicly release Symlink to facilitate future research.

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