A Computational Approach to Language Contact – A Case Study of Persian

Ali Basirat, Danial Namazifard, Navid Baradaran Hemmati


Abstract
We investigate structural traces of language contact in the intermediate representations of a monolingual language model. Focusing on Persian (Farsi) as a historically contact-rich language, we probe the representations of a Persian-trained model when exposed to languages with varying degrees and types of contact with Persian. Our methodology quantifies the amount of linguistic information encoded in intermediate representations and assesses how this information is distributed across model components for different morphosyntactic features. The results show that universal syntactic information is largely insensitive to historical contact, whereas morphological features such as CASE and GENDER are strongly shaped by language-specific structure, suggesting that contact effects in monolingual language models are selective and structurally constrained.
Anthology ID:
2026.silkroadnlp-1.5
Volume:
The Proceedings of the First Workshop on NLP and LLMs for the Iranian Language Family
Month:
March
Year:
2026
Address:
Rabat, Morocco
Editors:
Rayyan Merchant, Karine Megerdoomian
Venues:
SilkRoadNLP | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
38–49
Language:
URL:
https://aclanthology.org/2026.silkroadnlp-1.5/
DOI:
Bibkey:
Cite (ACL):
Ali Basirat, Danial Namazifard, and Navid Baradaran Hemmati. 2026. A Computational Approach to Language Contact – A Case Study of Persian. In The Proceedings of the First Workshop on NLP and LLMs for the Iranian Language Family, pages 38–49, Rabat, Morocco. Association for Computational Linguistics.
Cite (Informal):
A Computational Approach to Language Contact – A Case Study of Persian (Basirat et al., SilkRoadNLP 2026)
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PDF:
https://aclanthology.org/2026.silkroadnlp-1.5.pdf