The structure of the sight domain in Slavic: Bulgarian, Polish, and Russian verbs of visual perception in a parallel corpus

Abstract The paper offers a quantitative exploration of semantic relations between sight verbs in three Slavic languages – Bulgarian, Polish and Russian. Based on parallel-corpus data, I use the frequencies of pairwise correspondence between a broad range of sight verbs. The goal is to test the relevance of semantic distinctions typically drawn in typologically-oriented research on perception and to explore the semantic structure of the class in an empirically grounded way. First, the study addresses the relation between basic verbs and semantic generality. Basic and non-basic sight verbs within one language are compared with respect to their similarity to basic verbs of the other languages and in terms of the evenness of their correspondences to non-basic verbs in the other languages. The results show that the distinction between basic and non-basic verbs can be more or less clear-cut depending on the semantic type of verbs and on the language. Second, the distinction between ‘see’- and ‘look’-verbs was found relevant for the structuring on the domain of sight. Sight verbs are similar either to basic ‘see’-verbs or to ‘look’-verbs, or to neither of the two. There is more potential for lexical renewal among ‘look’-verbs as compared to ‘see’-verbs. Finally, the study shows that imperfective ‘look’-verbs more freely correspond to each other than perfectives, suggesting less clear semantic contrasts in the descriptions of ongoing perception as compared to the result of perception.

Authors

Institutions

Publication Details

Journal
Russian Linguistics
Published
2025-10-03
DOI
https://doi.org/10.1007/s11185-025-09323-9
Primary Topic
Categorization, perception, and language
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The structure of the sight domain in Slavic: Bulgarian, Polish, and Russian verbs of visual perception in a parallel corpus

Maria Ovsjannikova
Russian Linguistics
Categorization, perception, and language
article

The structure of the sight domain in Slavic: Bulgarian, Polish, and Russian verbs of visual perception in a parallel corpus

Maria Ovsjannikova
article en

Abstract

Abstract The paper offers a quantitative exploration of semantic relations between sight verbs in three Slavic languages – Bulgarian, Polish and Russian. Based on parallel-corpus data, I use the frequencies of pairwise correspondence between a broad range of sight verbs. The goal is to test the relevance of semantic distinctions typically drawn in typologically-oriented research on perception and to explore the semantic structure of the class in an empirically grounded way. First, the study addresses the relation between basic verbs and semantic generality. Basic and non-basic sight verbs within one language are compared with respect to their similarity to basic verbs of the other languages and in terms of the evenness of their correspondences to non-basic verbs in the other languages. The results show that the distinction between basic and non-basic verbs can be more or less clear-cut depending on the semantic type of verbs and on the language. Second, the distinction between ‘see’- and ‘look’-verbs was found relevant for the structuring on the domain of sight. Sight verbs are similar either to basic ‘see’-verbs or to ‘look’-verbs, or to neither of the two. There is more potential for lexical renewal among ‘look’-verbs as compared to ‘see’-verbs. Finally, the study shows that imperfective ‘look’-verbs more freely correspond to each other than perfectives, suggesting less clear semantic contrasts in the descriptions of ongoing perception as compared to the result of perception.

Russian LinguisticsVol. 49(1)
University of Potsdam (DE)
Universität Potsdam
Openalex Percentile: Top 72%
Categorization, perception, and language
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.