1. Idioms, Probing and Dangerous Things: Towards Structural Probing for Idiomaticity in Vector Space
- Author
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Klubička, Filip, Nedumpozhimana, Vasudevan, and Kelleher, John D.
- Subjects
FOS: Computer and information sciences ,Computer Science - Machine Learning ,Artificial Intelligence (cs.AI) ,Computer Science - Computation and Language ,Computer Science - Artificial Intelligence ,68T50 ,Computation and Language (cs.CL) ,Machine Learning (cs.LG) - Abstract
The goal of this paper is to learn more about how idiomatic information is structurally encoded in embeddings, using a structural probing method. We repurpose an existing English verbal multi-word expression (MWE) dataset to suit the probing framework and perform a comparative probing study of static (GloVe) and contextual (BERT) embeddings. Our experiments indicate that both encode some idiomatic information to varying degrees, but yield conflicting evidence as to whether idiomaticity is encoded in the vector norm, leaving this an open question. We also identify some limitations of the used dataset and highlight important directions for future work in improving its suitability for a probing analysis., 9 pages, 5 tables, In proceedings of the 19th Workshop on Multiword Expressions @ EACL2023
- Published
- 2023