Rodríguez-Fernández S, Espinosa-Anke L, Carlini R, Wanner L. Semantics-Driven Recognition of Collocations Using Word Embeddings. Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL 2016)

L2 learners often produce “ungrammatical” word combinations such as, e.g., *give a suggestion or *make a walk. This is because of the “collocationality” of one of their items (the base) that limits the acceptance of collocates to express a specific meaning (‘perform’ above). We propose an algorithm that delivers, for a given base and the intended meaning of a collocate, the actual collocate lexeme(s) (make / take above). The algorithm exploits the linear mapping between bases and collocates from examples and generates a collocation transformation matrix which is then applied to novel unseen cases. The evaluation shows a promising line of research in collocation discovery

Additional material:

• Open Access version at UPF e-repository
• Training data
• Script that emulates the experiment in T. Milokov's paper "Exploiting Similarities among Languages for Machine Translation" that we used for collocation discovery