MAGPIE: A Large Corpus of Potentially Idiomatic Expressions

Hessel Haagsma, Johan Bos, Malvina Nissim


Abstract
Given the limited size of existing idiom corpora, we aim to enable progress in automatic idiom processing and linguistic analysis by creating the largest-to-date corpus of idioms for English. Using a fixed idiom list, automatic pre-extraction, and a strictly controlled crowdsourced annotation procedure, we show that it is feasible to build a high-quality corpus comprising more than 50K instances, an order of a magnitude larger than previous resources. Crucial ingredients of crowdsourcing were the selection of crowdworkers, clear and comprehensive instructions, and an interface that breaks down the task in small, manageable steps. Analysis of the resulting corpus revealed strong effects of genre on idiom distribution, providing new evidence for existing theories on what influences idiom usage. The corpus also contains rich metadata, and is made publicly available.
Anthology ID:
2020.lrec-1.35
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:
279–287
Language:
English
URL:
https://www.aclweb.org/anthology/2020.lrec-1.35
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/2020.lrec-1.35.pdf