Large-Scale Bitext Corpora Provide New Evidence for Cognitive Representations of Spatial Terms

Peter Viechnicki, Kevin Duh, Anthony Kostacos, Barbara Landau


Abstract
Recent evidence from cognitive science suggests that there exist two classes of cognitive representations within the spatial terms of a language, one represented geometrically (e.g., above, below) and the other functionally (e.g., on, in). It has been hypothesized that geometric terms are more constrained and are mastered relatively early in language learning, whereas functional terms are less constrained and are mastered over longer time periods (Landau, 2016). One consequence of this hypothesis is that these two classes should exhibit different cross-linguistic variability, which is supported by human elicitation studies. In this work we present to our knowledge the first corpus-based empirical test of this hypothesis. We develop a pipeline for extracting, isolating, and aligning spatial terms in basic locative constructions from parallel text. Using Shannon entropy to measure the variability of spatial term use across eight languages, we find supporting evidence that variability in functional terms differs significantly from that of geometric terms. We also perform latent variable modeling and find support for the division of spatial terms into geometric and functional classes.
Anthology ID:
2024.eacl-long.66
Volume:
Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
March
Year:
2024
Address:
St. Julian’s, Malta
Editors:
Yvette Graham, Matthew Purver
Venue:
EACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1089–1099
Language:
URL:
https://aclanthology.org/2024.eacl-long.66
DOI:
Bibkey:
Cite (ACL):
Peter Viechnicki, Kevin Duh, Anthony Kostacos, and Barbara Landau. 2024. Large-Scale Bitext Corpora Provide New Evidence for Cognitive Representations of Spatial Terms. In Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers), pages 1089–1099, St. Julian’s, Malta. Association for Computational Linguistics.
Cite (Informal):
Large-Scale Bitext Corpora Provide New Evidence for Cognitive Representations of Spatial Terms (Viechnicki et al., EACL 2024)
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PDF:
https://aclanthology.org/2024.eacl-long.66.pdf
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