Grammatical Profiling for Semantic Change Detection
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Abstract (arXiv)
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.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 9 of its 32 references that are in the map. First posted on arXiv 21 Sep 2021.
Builds on
9 of 32 references.
References · 9
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
- 2013Distributed Representations of Words and Phrases and their Compositionalitycited by 3,462
- 2018Deep contextualized word representationscited by 2,285
- 2018WiC: the Word-in-Context Dataset for Evaluating Context-Sensitive Meaning Representationscited by 370
- 2020SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detectioncited by 105
- 2020Analysing Lexical Semantic Change with Contextualised Word Representationscited by 92
- 2018Diachronic word embeddings and semantic shifts: a surveycited by 90
- 2018Diachronic Usage Relatedness (DURel): A Framework for the Annotation of Lexical Semantic Changecited by 35
- 2021Three-part diachronic semantic change dataset for Russiancited by 11
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Citing papers per year: 2022: 3; 2023: 2; 2024: 1; 2025: 0; 2026: 4.
10 papers.
- 2023A Survey on Contextualised Semantic Shift Detectioncited by 21
- 2022Slangvolution: A Causal Analysis of Semantic Change and Frequency Dynamics in Slangcited by 14
- 2022LSCDiscovery: A shared task on semantic change discovery and detection in Spanishcited by 11
- 2023Can Word Sense Distribution Detect Semantic Changes of Words?cited by 10
- 2022Do Not Fire the Linguist: Grammatical Profiles Help Language Models Detect Semantic Changecited by 7
- 2024A Semantic Distance Metric Learning approach for Lexical Semantic Change Detectioncited by 5
- 2026Transparent Semantic Change Detection with Dependency-Based Profilescited by 3
- 2026ReFRAME or Remain: Unsupervised Lexical Semantic Change Detection with Frame Semanticscited by 2
- 2026SynFlow: A Multidimensional Diachronic Semantic Analysis Toolkitcited by 1
- 2026Evaluating the Evaluator: Problems with SemEval-2020 Task 1 for Lexical Semantic Change Detectioncited by 0
- 2026SynFlow: A Multidimensional Diachronic Semantic Analysis Toolkit19 Aug 2026
- 2026Evaluating the Evaluator: Problems with SemEval-2020 Task 1 for Lexical Semantic Change Detection14 Apr 2026
- 2026ReFRAME or Remain: Unsupervised Lexical Semantic Change Detection with Frame Semantics4 Feb 2026
- 2026Transparent Semantic Change Detection with Dependency-Based Profiles6 Jan 2026
- 2024A Semantic Distance Metric Learning approach for Lexical Semantic Change Detection1 Mar 2024
- 2023Can Word Sense Distribution Detect Semantic Changes of Words?16 Oct 2023
- 2023A Survey on Contextualised Semantic Shift Detection4 Apr 2023
- 2022LSCDiscovery: A shared task on semantic change discovery and detection in Spanish13 May 2022
- 2022Do Not Fire the Linguist: Grammatical Profiles Help Language Models Detect Semantic Change12 Apr 2022
- 2022Slangvolution: A Causal Analysis of Semantic Change and Frequency Dynamics in Slang9 Mar 2022