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NatCat: Weakly Supervised Text Classification with Naturally Annotated Resources
September 29, 2020 ยท Declared Dead ยท ๐ Conference on Automated Knowledge Base Construction
"No code URL or promise found in abstract"
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Authors
Zewei Chu, Karl Stratos, Kevin Gimpel
arXiv ID
2009.14335
Category
cs.CL: Computation & Language
Citations
5
Venue
Conference on Automated Knowledge Base Construction
Last Checked
4 months ago
Abstract
We describe NatCat, a large-scale resource for text classification constructed from three data sources: Wikipedia, Stack Exchange, and Reddit. NatCat consists of document-category pairs derived from manual curation that occurs naturally within online communities. To demonstrate its usefulness, we build general purpose text classifiers by training on NatCat and evaluate them on a suite of 11 text classification tasks (CatEval), reporting large improvements compared to prior work. We benchmark different modeling choices and resource combinations and show how tasks benefit from particular NatCat data sources.
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