Quantifying the cross-linguistic effects of syncretism on agreement attraction
Mirrored from arXiv — NLP / Computation & Language for archival readability. Support the source by reading on the original site.
Computer Science > Computation and Language
Title:Quantifying the cross-linguistic effects of syncretism on agreement attraction
Abstract:Agreement attraction errors, in which a verb erroneously agrees with an intervening noun rather than its grammatical head, are amplified by morphological syncretism in some languages (English, German, Russian) but not others (Turkish, Armenian), a cross-linguistic pattern without a principled account. We use surprisal and attention entropy from large language models as processing proxies to investigate this variation across four languages. LLM-derived measures replicate behavioral findings in English and German (syncretism modulates attraction), align with Turkish null results (no modulation), and partially capture Russian patterns. We discuss further directions for better understanding why syncretism affects agreement attraction differently across languages.
| Comments: | SCiL Conference Paper |
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2605.21403 [cs.CL] |
| (or arXiv:2605.21403v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2605.21403
arXiv-issued DOI via DataCite (pending registration)
|
Access Paper:
- View PDF
- TeX Source
References & Citations
Bookmark
Bibliographic and Citation Tools
Code, Data and Media Associated with this Article
Demos
Recommenders and Search Tools
arXivLabs: experimental projects with community collaborators
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.
Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
More from arXiv — NLP / Computation & Language
-
Shiny Stories, Hidden Struggles: Investigating the Representation of Disability Through the Lens of LLMs
May 21
-
Leveraging Large Language Models for Sentiment Analysis: Multi-Modal Analysis of Decentraland's MANA Token
May 21
-
Improving Quantized Model Performance in Qualitative Analysis with Multi-Pass Prompt Verification
May 21
-
Parallel LLM Reasoning for Bias-Resilient, Robust Conceptual Abstraction
May 21
Discussion (0)
Sign in to join the discussion. Free account, 30 seconds — email code or GitHub.
Sign in →No comments yet. Sign in and be the first to say something.