@article{hosseini-kivanani-philippy-2026-luxborrow,
    title = "{L}ux{B}orrow: From Pompier to Pompjee, Tracing Borrowing in {L}uxembourgish",
    author = "Hosseini-Kivanani, Nina  and
      Philippy, Fred",
    editor = "Piperidis, Stelios  and
      Bel, N{\'u}ria  and
      van den Heuvel, Henk  and
      Ide, Nancy  and
      Krek, Simon  and
      Toral, Antonio",
    journal = "International Conference on Language Resources and Evaluation",
    volume = "main",
    month = may,
    year = "2026",
    address = "Palma de Mallorca, Spain",
    publisher = "ELRA Language Resource Association",
    url = "https://preview.aclanthology.org/ingest-lrec/2026.lrec-main.249/",
    pages = "3171--3183",
    abstract = "We present LuxBorrow, a borrowing-first analysis of Luxembourgish (LU) news spanning 27 years (1999{--}2025): 259,305 RTL articles and 43.7M tokens. Our pipeline combines sentence-level language identification (LU/DE/FR/EN) with a token-level borrowing resolver restricted to LU sentences, using lemmatization, a collected loanword registry, and compiled morphological/orthographic rules. Empirically, LU remains the matrix language across all documents, while multilingual practice is pervasive: 77.1{\%} of articles include at least one donor language and 65.4{\%} use three or four. Breadth does not imply intensity: median code-mixing index (CMI) increases from 3.90 (LU+1) to only 7.00 (LU+3), indicating localized insertions rather than balanced bilingual text. Domain/period summaries show moderate but persistent mixing, with CMI rising from 6.1 (1999{--}2007) to a peak of 8.4 (2020). Token-level adaptations total 25,444 instances and exhibit a mixed profile: morphological 63.8{\%}, orthographic 35.9{\%}, lexical 0.3{\%}; the most frequent single rules are orthographic (on{\textrightarrow}oun, eur{\textrightarrow}er), while morphology is collectively dominant. Diachronically, code-switching intensifies, and morphologically adapted borrowings grow from a small base; French overwhelmingly supplies adapted items, with modest growth for German and negligible English. We advocate borrowing-centric evaluation, borrowed token/type rates, donor entropy over borrowed items, and assimilation ratios over headline document-level mixing indices."
}