The ACL OCL Corpus: Advancing Open Science in Computational Linguistics
Rohatgi, Shaurya, Qin, Yanxia, Aw, Benjamin, Unnithan, Niranjana, Kan, Min-Yen
–arXiv.org Artificial Intelligence
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).
arXiv.org Artificial Intelligence
Oct-24-2023
- Country:
- Africa > Middle East
- Morocco (0.04)
- Asia
- Europe
- Czechia > Prague (0.04)
- Germany > Berlin (0.04)
- Ireland > Leinster
- County Dublin > Dublin (0.04)
- Portugal > Lisbon
- Lisbon (0.04)
- Slovenia (0.04)
- Spain > Catalonia
- Barcelona Province > Barcelona (0.04)
- United Kingdom > England
- Greater Manchester > Manchester (0.04)
- North America
- Dominican Republic (0.04)
- United States
- Hawaii > Honolulu County
- Honolulu (0.04)
- Minnesota > Hennepin County
- Minneapolis (0.14)
- New York > New York County
- New York City (0.04)
- Pennsylvania (0.04)
- Washington > King County
- Seattle (0.04)
- Hawaii > Honolulu County
- Africa > Middle East
- Genre:
- Research Report (0.40)
- Technology: