The ACL OCL Corpus: Advancing Open Science in Computational Linguistics

Shaurya Rohatgi, Yanxia Qin, Benjamin Aw, Niranjana Anand Unnithan, Min-Yen Kan

Submission Type: Regular Long Paper

Submission Track: Resources and Evaluation

Keywords: scholarly corpus, computational linguistics, topic trend analysis, acl anthology

TL;DR: We present ACL OCL (https://huggingface.co/datasets/WINGNUS/ACL-OCL), a scholarly corpus derived from the ACL Anthology to assist Open scientific research in the Computational Linguistics domain.

Abstract:

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).

Submission Number: 2901