Using Linguistic Resources to Evaluate the Quality of Annotated Corpora

Max Silberztein


Abstract
Statistical and neural-network-based methods that compute their results by comparing a given text to be analyzed with a reference corpus assume that the reference corpus is complete and reliable enough. In this article, I conduct several experiments on an extract of the Open American National Corpus to verify this assumption.
Anthology ID:
W18-3802
Volume:
Proceedings of the First Workshop on Linguistic Resources for Natural Language Processing
Month:
August
Year:
2018
Address:
Santa Fe, New Mexico, USA
Venues:
COLING | LR4NLP | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
2–11
Language:
URL:
https://www.aclweb.org/anthology/W18-3802
DOI:
Bib Export formats:
BibTeX MODS XML EndNote
PDF:
http://aclanthology.lst.uni-saarland.de/W18-3802.pdf