Papers › AMALGUM -- A Free, Balanced, Multilayer English Web Corpus
AMALGUM -- A Free, Balanced, Multilayer English Web Corpus
Luke Gessler, Siyao Peng, Yang Liu, YIlun Zhu, Shabnam Behzad, Amir Zeldes
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.
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