Supervision versus Demonstration-Based In-Context Learning for Multiword Expression Classification
Turkish idiomatic light verb constructions (LVCs) are challenging for multiword expression processing because they often share the same surface form as fully literal verb-object combinations while functioning as a single, partially idiomatic predicate. We frame Turkish LVC detection as a binary classification task (literal meaning vs. idiomatic meaning) and evaluate on a manually created controlled set (N=147) with matched negatives: out-of-domain random sentences and in-domain literal controls (NLVC), alongside LVC positives. We compare a supervised Turkish encoder baseline (BERTurk with a classifier head) to three instruction-tuned LLMs from different families under zero-shot, one-shot,...
| Authors | Sercan Karakaş, Yusuf Şimşek |
|---|---|
| Primary category | cs.CL |
| Published | 5 June 2026 |
| Last updated at source | 5 June 2026 |
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