--- title: "LombardoGraphia — Signoroni 2026" description: "Lombard, which has roughly 3.8 million speakers across Northern Italy and Southern Switzerland, has no single agreed spelling standard." authors: ["Edoardo Signoroni", "Pavel Rychly"] year: 2026 venue: "Proceedings of the Fifteenth Language Resources and Evaluation Conference" source: "https://aclanthology.org/2026.lrec-1.257/" doi: "10.63317/2vm9gj2ap9wq" licence: "CC BY-NC 4.0 (ELRA, LREC proceedings)" licence_url: "https://creativecommons.org/licenses/by-nc/4.0/" summary_licence: "Elamur Cosmic License" canonical: "https://research.elamur.ai/free/en/papers/signoroni-2026-lombardographia-automatic-classification-lombard-orthography/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/signoroni-2026-lombardographia-automatic-classification-lombard-orthography/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [2026](https://md.research.elamur.ai/free/en/papers/2026/page/6/) / LombardoGraphia: Automatic Classification of Lombard Orthography Variants # LombardoGraphia: Automatic Classification of Lombard Orthography Variants **Authors:** [Edoardo Signoroni](https://md.research.elamur.ai/free/en/authors/edoardo-signoroni/), [Pavel Rychly](https://md.research.elamur.ai/free/en/authors/pavel-rychly/) · **Year:** 2026 · **Venue:** Proceedings of the Fifteenth Language Resources and Evaluation Conference · **Licence:** [CC BY-NC 4.0 (ELRA, LREC proceedings)](https://creativecommons.org/licenses/by-nc/4.0/) **Links:** [Publisher's page](https://aclanthology.org/2026.lrec-1.257/) · [PDF](https://aclanthology.org/2026.lrec-1.257.pdf) · [DOI 10.63317/2vm9gj2ap9wq](https://doi.org/10.63317/2vm9gj2ap9wq) · [OpenAlex](https://openalex.org/W7160202076) **Citations:** 1 citations (openalex-snapshot · 2026-10-14) ## Summary Lombard, which has roughly 3.8 million speakers across Northern Italy and Southern Switzerland, has no single agreed spelling standard. Writers use competing orthographies, so collecting data for NLP risks blending distinct varieties without noticing. The authors frame the task of identifying which orthography a text uses as a necessary step toward building separate corpora for each variety without imposing an artificial norm. They present LombardoGraphia, built from Lombard Wikipedia content that was cleaned and filtered to keep material usable for orthographic analysis. Each sample is labelled with one of nine spelling systems. These range from pan-Lombard polynomic systems to macro-dialectal and strictly local conventions. On this data they train and compare 24 classifiers, covering both classical and neural approaches with different feature types and encoding granularities. The strongest systems reach roughly 96% overall accuracy, but their per-class average is clearly lower. This gap shows that rare orthographies remain difficult because the data are imbalanced. The released resources give a first benchmark and practical tooling for variety-aware Lombard NLP. ## Key points - The corpus contains 11,186 Lombard Wikipedia samples labelled with 9 orthographies, split into train, validation and test sets. - Pan-Lombard: NOL, SL. - Macro-dialectal: LOCC, LORUNIF. - Local: MILCLASS, BERGDUC, LSI, BREMOD, CRES. - The corpus includes metadata describing each orthographic system and its geographic distribution. - The authors evaluate 24 traditional and neural classification models. - The best models score 96.06% overall accuracy and 85.78% average class accuracy. Minority orthographies remain the main weakness. - The corpus, models and code are published as lmo_graphia on GitHub (edoardosignoroni/lmo_graphia). The authors suggest uses in corpus building, language identification and orthographic normalization. *Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.* Fields: [Linguistics & languages](https://md.research.elamur.ai/free/en/shelves/linguistics/) ## Cite The paper itself, not this page. BibTeX from the library's record of the work. ```bibtex @inproceedings{signoroni2026lombardographia, title = {{LombardoGraphia: Automatic Classification of Lombard Orthography Variants}}, author = {Signoroni, Edoardo and Rychly, Pavel}, booktitle = {Proceedings of the Fifteenth Language Resources and Evaluation Conference}, year = {2026}, doi = {10.63317/2vm9gj2ap9wq}, url = {https://doi.org/10.63317/2vm9gj2ap9wq} } ``` - [← previous Logic-Level Evaluation of Logical Table-to-Text Generation](https://md.research.elamur.ai/free/en/papers/trigg-2026-logic-level-evaluation-logical-table/) - [next → LongTailQA: Benchmarking LLMs and RAG Models on Disambiguated Long-Tail Entities](https://md.research.elamur.ai/free/en/papers/xion-2026-longtailqa-benchmarking-llms-rag-models/) - [↑ back to papers of 2026](https://md.research.elamur.ai/free/en/papers/2026/page/6/) ## References 26 references, 1 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet. 1. 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