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Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      Schema at index 1 was different: 
features: struct<corpus: string, counter_tokens: struct<est: int64, est_hiiu_ekidct: int64>, filename: string, text_type: list<item: string>>
sentences: list<item: struct<est: string, est_hiiu_ekidct: string>>
vs
features: struct<corpus: string, counter_tokens: struct<est: int64, est_kihnu_ekidct: int64>, filename: string, text_type: list<item: string>>
sentences: list<item: struct<est: string, est_kihnu_ekidct: string>>
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 243, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 3496, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2257, in _head
                  return next(iter(self.iter(batch_size=n)))
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2461, in iter
                  for key, example in iterator:
                                      ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1952, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1974, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 531, in _iter_arrow
                  yield new_key, pa.Table.from_batches(chunks_buffer)
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "pyarrow/table.pxi", line 5039, in pyarrow.lib.Table.from_batches
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: Schema at index 1 was different: 
              features: struct<corpus: string, counter_tokens: struct<est: int64, est_hiiu_ekidct: int64>, filename: string, text_type: list<item: string>>
              sentences: list<item: struct<est: string, est_hiiu_ekidct: string>>
              vs
              features: struct<corpus: string, counter_tokens: struct<est: int64, est_kihnu_ekidct: int64>, filename: string, text_type: list<item: string>>
              sentences: list<item: struct<est: string, est_kihnu_ekidct: string>>

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Dataset Card for language_relatives_2025

Dataset Summary

The dataset is a collection of mono- and multilingual text corpora of many language relatives of standard Estonian, i.e. Finno-Ugric languages and dialects, excluding Finnish and Hungarian. Multilingual corpora include other languages as translation equivalents, among them also Estonian, Finnish and Hungarian.

The aim is to provide data for language technology, first and foremost for machine translation.

Languages

Finno-Ugric language relatives

ISO 639-3 Language Tokens
fit Tornedalen Finnish (Meänkieli) 8750
fkv Kven (Kven Finnish) 55506
izh Ingrian (= Izhorian) 249093
kca Khanty 97611
koi Komi-Permyak 382071
kpv Komi-Zyrian 18194967
krl Karelian (Proper Karelian) 981158
liv Livonian 15035
lud Ludian 291293
mdf Moksha 822508
mhr Meadow Mari 6360111
mns Mansi 263280
mrj Hill Mari 1494257
myv Erzya 2526670
olo Livvi-Karelian (Olonets) 1245935
sjd Kildin Sami 1338
sju Ume Sami 619
sma Southern Sami 1703932
sme Northern Sami 21540241
smj Lule Sami 950311
smn Inari Sami 1217515
sms Skolt Sami 380250
udm Udmurt 1294508
vep Veps 2383752
vot Votic 48107
vro Võro 3266531

Estonian dialects

Dialect Tokens
hiiu 9095
kihnu 66001
mulgi 26895
ranna 9887
setu 283598

Languages of translation equivalents

ISO 639-3 Language Tokens
deu German 5729
eng English 26160
est Estonian 1937069
fin Finnish 1690382
fra French 6300
hun Hungarian 1573
lav Latvian 1529
nno Norwegian Nynorsk 1734
nob Norwegian Bokmål 5466
nor Norwegian 4425857
rus Russian 23503423
swe Swedish 6002

Dataset Structure

Texts are represented in JSON. The structures, keys and values are defined in pydantic_for_lingrel2025.py

Textual material may be a collection of linguistic units with different granularity and coherence. This dataset differentiates between:

  • unrelated words and phrases (e.g. a dictionary or a phrasebook)
  • unrelated sentences (e.g. a dictionary or a phrasebook)
  • coherent sequence of paragraphs and sentences (e.g. a novel with structural mark-up)
  • coherent text without explicit split into sentences

Any of these might be applicable to a monolingual or multilingual source, i.e. a text with translation(s).

In addition to granularity and mono/multilinguality, the dataset contains info about the dialect and orthography, and info about the original - author, title, publication year etc, and source - corpus, web page, file name etc.

Every file in this dataset has the text itself plus metainfo detailing all the info about this text.

The data is organised into directories. A file path name contains the following parts:

ISO code for language / "mono" or "multi" / eponym from source corpus name / eponym from source file name

Dataset Creation

Original texts have been transformed into JSON. Depending on the nature of the source, there are four classes:

  1. Unrelated words and phrases
  2. Unrelated sentences
  3. Coherent sequence of paragraphs and sentences
  4. Coherent text without explicit split into sentences

Source data that was impossible to map into any of these classes was left out. In some cases the language of the source text was additionally checked with GlotLID, and wrong language texts were left out. The orthography has not been checked nor modified.

Source Data

The dataset is built from various pre-existing publications and corpora: corpus_source.md

Licensing Information

All original textual content is licensed under a Creative Commons License (depending on the source, either CC-BY, CC-BY-SA, CC-BY-NC or CC-BY-NC-SA) or an equivalently permissible licence, or into the public domain.

Citation Information

@InProceedings{smugri4mt,
    title={SMUGRI-4: Machine-Translating Low-resource Finno-Ugric Languages and Dialects with Care and Caution},
    authors={Lisa Yankovskaya and Mark Fishel and Elena Markus and Fedor Rozhanskiy and Heiki-Jaan Kaalep and
        Idaliia Fedotova and Ilia Moshnikov and Janek Vaab and Joshua Wilbur and Liisa Rätsep and Marili Tomingas and
        Michael Rie{\ss}ler and Nikolay Kuznetsov and Taido Purason and Valts Ern\v{s}treits },
    year={2025},
    booktitle={Proceedings of EACL, the 19th Conference of the European Chapter of the
        Association for Computational Linguistics: System Demonstrations},
    pages={submitted},
    address={Rabat, Morocco}
}

Contributions

The following people have contributed by collecting or processing the original data:

Britt-Kathleen Mere, Aleksei Ivanov, Tarmo Vaino, Annely-Maria Liivas, Kaire Koljal, Lisa Yankovskaya, Heiki-Jaan Kaalep, Mark Fišel

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