Work

Grammatical Profiling for Semantic Change Detection

Year: 2021

Type: conference-paper

Abstract: 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.

Source: Conference on Computational Natural Language Learning

DOI: 10.18653/v1/2021.conll-1.33

Authors: Andrey Kutuzov, Lidia Pivovarova, Mario Giulianelli

Institutions: University of Helsinki, University of Oslo, University of Amsterdam

Language: English

Topic: Syntax, Semantics, Linguistic Variation

Subfield: Language and Linguistics

Field: Arts and Humanities

Domain: Social Sciences

Open Access status: hybrid

Funder: European Commission

Awards: G2388848714, G434337789, NewsEye: A Digital Investigator for Historical Newspapers, Cross-Lingual Embeddings for Less-Represented Languages in European News Media