Generation of a Spanish Artificial Collocation Error Corpus
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)
Abstract
Collocations such as heavy rain or make [a] decision are combinations of two elements where one (the base) is freely chosen, while the choice of the other (collocate) is restricted by the base. Research has consistently shown that collocations present difficulties even to the most advanced language learners, so that computational tools aimed at supporting them in the process of language learning can be of great value. However, in contrast to grammatical error detection and correction, collocation error marking and correction has not yet received the attention it deserves. This is unsurprising, considering the lack of existing collocation resources, in particular those that capture the different types of collocation errors, and the high cost of a manual creation of such resources. In this paper, we present an algorithm for the automatic generation of an artificial collocation error corpus of American English learners of Spanish that includes 17 different types of collocation errors and that can be used for automatic detection and classification of collocation errors in the writings of Spanish language learners.