# Grammatical Profiling for Semantic Change Detection

arXiv: https://arxiv.org/abs/2109.10397 · HTML: https://mlsanity.com/paper/2109.10397/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 32 references that are in the map.
- First posted on arXiv 21 Sep 2021.

## Builds on (most cited first, 9 of 9)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Distributed Representations of Words and Phrases and their Compositionality](https://mlsanity.com/paper/1310.4546/) (2013)
- [Deep contextualized word representations](https://mlsanity.com/paper/1802.05365/) (2018)
- [WiC: the Word-in-Context Dataset for Evaluating Context-Sensitive Meaning Representations](https://mlsanity.com/paper/1808.09121/) (2018)
- [SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection](https://mlsanity.com/paper/2007.11464/) (2020)
- [Diachronic word embeddings and semantic shifts: a survey](https://mlsanity.com/paper/1806.03537/) (2018)
- [Analysing Lexical Semantic Change with Contextualised Word Representations](https://mlsanity.com/paper/2004.14118/) (2020)
- [Diachronic Usage Relatedness (DURel): A Framework for the Annotation of Lexical Semantic Change](https://mlsanity.com/paper/1804.06517/) (2018)
- [Three-part diachronic semantic change dataset for Russian](https://mlsanity.com/paper/2106.08294/) (2021)

## Built on by (most cited first, 10 of 10)

- [A Survey on Contextualised Semantic Shift Detection](https://mlsanity.com/paper/2304.01666/) (2023)
- [Slangvolution: A Causal Analysis of Semantic Change and Frequency Dynamics in Slang](https://mlsanity.com/paper/2203.04651/) (2022)
- [LSCDiscovery: A shared task on semantic change discovery and detection in Spanish](https://mlsanity.com/paper/2205.06691/) (2022)
- [Can Word Sense Distribution Detect Semantic Changes of Words?](https://mlsanity.com/paper/2310.10400/) (2023)
- [Do Not Fire the Linguist: Grammatical Profiles Help Language Models Detect Semantic Change](https://mlsanity.com/paper/2204.05717/) (2022)
- [A Semantic Distance Metric Learning approach for Lexical Semantic Change Detection](https://mlsanity.com/paper/2403.00226/) (2024)
- [Transparent Semantic Change Detection with Dependency-Based Profiles](https://mlsanity.com/paper/2601.02891/) (2026)
- [ReFRAME or Remain: Unsupervised Lexical Semantic Change Detection with Frame Semantics](https://mlsanity.com/paper/2602.04514/) (2026)
- [Evaluating the Evaluator: Problems with SemEval-2020 Task 1 for Lexical Semantic Change Detection](https://mlsanity.com/paper/2604.13232/) (2026)
- [SynFlow: A Multidimensional Diachronic Semantic Analysis Toolkit](https://mlsanity.com/paper/2608.19472/) (2026)

## 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.