The ACL OCL Corpus: Advancing Open Science in Computational Linguistics
This dataset addresses the need for accessible, structured resources for researchers in computational linguistics, though it is incremental as it builds on existing ACL Anthology versions.
The authors introduced ACL OCL, a comprehensive scholarly corpus derived from the ACL Anthology to support open science in computational linguistics, containing 73K papers and 210K figures spanning seven decades, and demonstrated its utility by analyzing trends such as the decline in syntax topics and resurgence in natural language generation.
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 (https://huggingface.co/datasets/WINGNUS/ACL-OCL).