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ZurichNLP/mediomatix

published by @ZurichNLP

Alignment dataset tracked in the /datasets sub-catalog.

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19.8 MB
Created on HF
2025-07-22
Age
1 years ago

Description

General Information

Release of the Mediomatix corpus, prepared by UZH and PHGR, to be used for research purposes only.

Each segment is presented as part of a multi-parallel alignment. For the full, unaligned Mediomatix data in each idiom's schoolbooks, see here .

We use the following Romansh idiom codes as columns:

Sursilvan: rm-sursilv

Sutsilvan: rm-sutsilv

Surmiran: rm-surmiran

Puter: rm-puter

Vallader: rm-vallader

Book names are encoded in the book column as follows:

The… See the full description on the dataset page: https://huggingface.co/datasets/ZurichNLP/mediomatix.

Tags

language:rmlicense:cc-by-nc-sa-4.0size_categories:10K<n<100Kformat:jsonmodality:textlibrary:datasetslibrary:pandaslibrary:mlcroissantlibrary:polarsregion:us

README current version from Hugging Face


license: cc-by-nc-sa-4.0
language:

  • rm
    configs:
    • config_name: default
      data_files:
      • split: train
        path: train.jsonl
      • split: validation
        path: valid.jsonl
      • split: test
        path: test.jsonl
      • split: no_surm
        path: no_surm.jsonl

General Information

Release of the Mediomatix corpus, prepared by UZH and PHGR, to be used for research purposes only.

Each segment is presented as part of a multi-parallel alignment. For the full, unaligned Mediomatix data in each idiom's schoolbooks, see here .

We use the following Romansh idiom codes as columns:

  • Sursilvan: rm-sursilv
  • Sutsilvan: rm-sutsilv
  • Surmiran: rm-surmiran
  • Puter: rm-puter
  • Vallader: rm-vallader

Book names are encoded in the book column as follows:

  • The first digit refers to the school year of the book
  • The next refers to the book volums for that school year
  • The two letter code indicates whether the segment comes from the student workbook ("wb") or teacher's commentary ("tc")
  • Example: Book "5.1_tc" refers to teacher's commentary for Volume 1 of the year 5 schoolbook.

How to Use

To access all four splits, use the following code:

from datasets import load_dataset

# Load aligned dataset

mediomatix = load_dataset("ZurichNLP/mediomatix")

# Access Train set:

train_set = mediomatix['train']

# Access Validation set:

val_set = mediomatix['validation']

# Access Test set:

test_set = mediomatix['test']

# Access no-rm-surmiran split:

no_surm = mediomatix['no_surm']

Citation

@inproceedings{hopton-etal-2026-mediomatix,
    title = "The Mediomatix Corpus: Parallel Data for {R}omansh Language Varieties via Comparable Schoolbooks",
    author = {Hopton, Zachary William  and
      Vamvas, Jannis  and
      B{\"u}chler, Andrin  and
      Rutkiewicz, Anna  and
      Cathomas, Rico  and
      Sennrich, Rico},
    editor = "Demberg, Vera  and
      Inui, Kentaro  and
      Marquez, Llu{\'i}s",
    booktitle = "Findings of the {A}ssociation for {C}omputational {L}inguistics: {EACL} 2026",
    month = mar,
    year = "2026",
    address = "Rabat, Morocco",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2026.findings-eacl.16/",
    pages = "290--306",
    ISBN = "979-8-89176-386-9"
}

© 2025 Meds d'instrucziun dal Grischun

README history 17 revisions

Every night we snapshot the README of every dataset in the catalog. When the SHA changes we archive the new version and diff it against the last. This is the evolving thought record of the alignment-data field: what the author decided to say about the corpus, and how that framing shifted over time.

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Community discussions 1 thread · 1 open · 1 comments

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Metadata

License
cc-by-nc-sa-4.0

Repository

Download the dataset

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Copy any of these snippets into your notebook or terminal. All three fetch directly from Hugging Face using your own credentials.

Recommended: datasets library (Python)
from datasets import load_dataset
ds = load_dataset("ZurichNLP/mediomatix")
Raw snapshot (Python)
from huggingface_hub import snapshot_download
snapshot_download(repo_id="ZurichNLP/mediomatix", repo_type="dataset")
git clone (requires git-lfs)
git clone https://huggingface.co/datasets/ZurichNLP/mediomatix
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