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Automatic detection of unexpected/erroneous collocations in learner corpus

Abstract : This research investigates the collocational errors made by English learners in a learner corpus. It focuses on the extraction of unexpected collocations. A system was proposed and implemented with open source toolkit. Firstly, the collocation extraction module was evaluated by a corpus with manually annotated collocations. Secondly, a standard collocation list was collected from a corpus of native speaker. Thirdly, a list of unexpected collocations was generated by extracting candidates from a learner corpus and discarding the standard collocations on the list. The overall performance was evaluated, and possible sources of error were pointed out for future improvement.
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Contributor : Thomas Gaillat Connect in order to contact the contributor
Submitted on : Wednesday, February 17, 2021 - 12:35:10 PM
Last modification on : Sunday, January 2, 2022 - 4:34:01 PM
Long-term archiving on: : Tuesday, May 18, 2021 - 6:02:31 PM


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  • HAL Id : hal-03129858, version 1


Jen-Yu Li, Thomas Gaillat. Automatic detection of unexpected/erroneous collocations in learner corpus. COLING-MWE 2020, Dec 2020, Barcelona, Spain. pp.101--106. ⟨hal-03129858⟩



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