Grammatical Profiling for Semantic Change Detection
About
Semantics, morphology and syntax are strongly interdependent. However, the majority of computational methods for semantic change detection use distributional word representations which encode mostly semantics. We investigate an alternative method, grammatical profiling, based entirely on changes in the morphosyntactic behaviour of words. We demonstrate that it can be used for semantic change detection and even outperforms some distributional semantic methods. We present an in-depth qualitative and quantitative analysis of the predictions made by our grammatical profiling system, showing that they are plausible and interpretable.
Mario Giulianelli, Andrey Kutuzov, Lidia Pivovarova• 2021
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Lexical Semantic Change Detection | SemEval Task 1 Subtask 2 English 2020 | Spearman Correlation0.218 | 54 | |
| Binary Lexical Semantic Change Detection | SemEval Subtask 1 (English) 2020 | Accuracy0.622 | 28 |
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