Grammatical Profiling for Semantic Change Detection
This addresses semantic change detection for computational linguistics, offering an interpretable alternative to existing methods.
The paper tackled the problem of semantic change detection by proposing grammatical profiling, a method based on morphosyntactic behavior changes, and found that it outperforms some distributional semantic methods.
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.