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The ACL OCL Corpus: Advancing Open Science in Computational Linguistics
Conference proceeding

The ACL OCL Corpus: Advancing Open Science in Computational Linguistics

Shaurya Rohatgi, Yanxia Qin, Benjamin Aw, Niranjana Unnithan and Min-Yen Kan
2023 CONFERENCE ON EMPIRICAL METHODS IN NATURAL LANGUAGE PROCESSING (EMNLP 2023), pp.10348-10361
01/01/2023

Abstract

Computer Science Computer Science, Artificial Intelligence Computer Science, Interdisciplinary Applications Linguistics Science & Technology Social Sciences Technology
We present ACL OCL, a scholarly corpus derived from the ACL Anthology to assist Open scientific research in the Computational Linguistics domain. Integrating and enhancing the previous versions of the ACL Anthology, the ACL OCL contributes metadata, PDF files, citation graphs and additional structured full texts with sections, figures, and links to a large knowledge resource (Semantic Scholar). The ACL OCL spans seven decades, containing 73K papers, alongside 210K figures. We spotlight how ACL OCL applies to observe trends in computational linguistics. By detecting paper topics with a supervised neural model, we note that interest in "Syntax: Tagging, Chunking and Parsing" is waning and "Natural Language Generation" is resurging. Our dataset is available from HuggingFace.

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