AMALGUM – A Free, Balanced, Multilayer English Web Corpus

Luke Gessler, Siyao Peng, Yang Liu, Yilun Zhu, Shabnam Behzad, Amir Zeldes


Abstract
We present a freely available, genre-balanced English web corpus totaling 4M tokens and featuring a large number of high-quality automatic annotation layers, including dependency trees, non-named entity annotations, coreference resolution, and discourse trees in Rhetorical Structure Theory. By tapping open online data sources the corpus is meant to offer a more sizable alternative to smaller manually created annotated data sets, while avoiding pitfalls such as imbalanced or unknown composition, licensing problems, and low-quality natural language processing. We harness knowledge from multiple annotation layers in order to achieve a “better than NLP” benchmark and evaluate the accuracy of the resulting resource.
Anthology ID:
2020.lrec-1.648
Volume:
Proceedings of the 12th Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Venues:
COLING | LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
5267–5275
Language:
English
URL:
https://www.aclweb.org/anthology/2020.lrec-1.648
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/2020.lrec-1.648.pdf