Datasets:

mschonhardt
/

georges-1913-normalization

Error code:   DatasetGenerationError
Exception:    ParserError
Message:      Error tokenizing data. C error: Expected 2 fields in line 288813, saw 3

Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1854, in _prepare_split_single
                  for _, table in generator:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/csv/csv.py", line 190, in _generate_tables
                  for batch_idx, df in enumerate(csv_file_reader):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 1843, in __next__
                  return self.get_chunk()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 1985, in get_chunk
                  return self.read(nrows=size)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 1923, in read
                  ) = self._engine.read(  # type: ignore[attr-defined]
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 234, in read
                  chunks = self._reader.read_low_memory(nrows)
                File "parsers.pyx", line 850, in pandas._libs.parsers.TextReader.read_low_memory
                File "parsers.pyx", line 905, in pandas._libs.parsers.TextReader._read_rows
                File "parsers.pyx", line 874, in pandas._libs.parsers.TextReader._tokenize_rows
                File "parsers.pyx", line 891, in pandas._libs.parsers.TextReader._check_tokenize_status
                File "parsers.pyx", line 2061, in pandas._libs.parsers.raise_parser_error
              pandas.errors.ParserError: Error tokenizing data. C error: Expected 2 fields in line 288813, saw 3
              
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1417, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1049, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 924, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1000, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1741, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1897, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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lallantum string	lallantum.1 string
exambieram	exambieram
circumcalcabicis	circumcalcabitis
peruincaturi	pervincaturi
tepidaremtur	tepidarentur
exmovemdis	exmovendis
comvomavisset	convomavisset
permeiemdis	permeiendis
permeditacissime	permeditatissime
conspersu	conspersu
pręviridancissimę	praeviridantissimae
relaxavisses	relaxavisses
edentaveratis	edentaveratis
amhelioris	anhelioris
remediatae	remediatae
discruciavero	discruciavero
imterplicavimus	interplicavimus
peraequata	peraequata
ignicomantissimorum	ignicomantissimorum
pręfvltvro	praefulturo
subsentiauere	subsentiavere
deferbuisse	deferbuisse
sufficieims	sufficieins
agglomeraturus	agglomeraturus
ceuebam	cevebam
pręveniaveratis	praeveniaveratis
subornemus	subornemus
deserviecis	deservietis
fibvlatis	fibulatis
Stoice	Stoice
diremptissimarum	diremptissimarum
imspuature	inspuature
simulaijus	simulaiius
concavandvm	concavandum
comseptaret	conseptaret
queritantur	queritantur
Pseudodecimiamius	Pseudodecimianius
clocitavere	clocitavere
delingendarum	delingendarum
inceptivissimorvm	inceptivissimorum
deletas	deletas
denominauero	denominavero
oblaqveanto	oblaqueanto
suffulcitur	suffulcitur
laboratvr	laboratur
Stilbonis	Stilbonis
belligerauissent	belligeravissent
inseminaturos	inseminaturos
Calliphoncis	Calliphontis
derepavissent	derepavissent
Themiscyram	Themiscyram
coartaueram	coartaveram
Cęissime	Caeissime
ardebicis	ardebitis
Utis	Utis
despermatam	despernatam
conscitutoriarum	constitutoriarum
tinniliissimum	tinniliissimum
comciliatum	conciliatum
commingis	commingis
conchyliato	conchyliato
saetigerrima	saetigerrima
sanctescet	sanctescet
mvltabit	multabit
Gygęiori	Gygaeiori
amxiosiora	anxiosiora
impvrpvratissimvs	impurpuratissimus
cermularer	cernularer
imterplicature	interplicature
combvstionem	combustionem
permulcendus	permulcendus
perjistis	periistis
conspoliares	conspoliares
pręrvptiora	praeruptiora
ambigentissimarvm	ambigentissimarum
monstraciora	monstratiora
praefigvrabimini	praefigurabimini
svperlatissime	superlatissime
monasticissimis	monasticissimis
triplijorvm	tripliiorum
meclegeijoribus	neclegeiioribus
exsvperabilie	exsuperabilie
lvtosissimis	lutosissimis
aduentem	adventem
albicascatvra	albicascatura
comflabas	conflabas
superenatandam	superenatandam
consideracionem	considerationem
tibizabam	tibizabam
quattuorangulatiljioribus	quattuorangulatiliioribus
incoles	incoles
desulcarent	desulcarent
consauciavisti	consauciavisti
circvmtenvimvs	circumtenuimus
svbvelavissent	subvelavissent
interqviescaveris	interquiescaveris
comfumeramtem	confunerantem
admencirentur	admentirentur
abnodavimus	abnodavimus
Vnde Unde	null
demormavimus	denormavimus

End of preview.

Normalized Georges 1913

Description

This dataset was created as part of the Burchard's Dekret Digital project (www.burchards-dekret-digital.de), funded by the Academy of Sciences and Literature | Mainz.

It is based on 55,000 lemmata from Karl Georges, Ausführliches lateinisch-deutsches Handwörterbuch, Hannover 1913 (Georges 1913) and was developed to train models for normalization tasks in the context of medieval Latin.

The dataset consists of approximately 5 million word pairs of orthographic variants alongside their normalized forms. These word pairs were generated by introducing systematic orthographic transformations, such as:

v ↔ u substitutions: Interchanging v and u.
ii → ij / ii → ji substitutions: Modifying digraphs (ii) into alternative medieval forms (ij, ji).
ae → ę replacements: Replacing ae with ę.
ti → ci substitutions: Transforming ti into ci.
mn → mpn modifications: Expanding mn to mpn.
n → m changes: Replacing n with m.
y → i replacements: Substituting y with i.

These transformations were designed to provide a dataset for text normalization of medieval Latin manuscript transcriptions.

Dataset Structure

The dataset is formatted as tab-separated pairs where each line contains an orthographic variant followed by its normalized form, e.g.:

Ortographical variant	normalized form
`circumcalcabicis`	`circumcalcabitis`
`peruincaturi`	`pervincaturi`
`tepidaremtur`	`tepidarentur`
`exmovemdis`	`exmovendis`
`comvomavisset`	`convomavisset`
`permeiemdis`	`permeiendis`
`permeditacissime`	`permeditatissime`
`conspersu`	`conspersu`
`pręviridancissimę`	`praeviridantissimae`
`relaxavisses`	`relaxavisses`
`edentaveratis`	`edentaveratis`
`amhelioris`	`anhelioris`
`remediatae`	`remediatae`
`discruciavero`	`discruciavero`
`imterplicavimus`	`interplicavimus`
`peraequata`	`peraequata`
`ignicomantissimorum`	`ignicomantissimorum`
`pręfvltvro`	`praefulturo`

Usecases

This dataset can be used for:

Training normalization models for medieval Latin texts.
Developing text restoration or correction tools for historical documents.
Applying normalization based on Georges 1913.

Known limitations

The dataset has not been subjected to data augmentation and may contain substantial bias, particularly against irregular forms, such as Greek loanwords like "presbyter."

Data Splits

The dataset consists of a single shuffled split of 5 million word pairs. Users can create their own train/validation/test splits depending on their use case.

Acknowledgments

Dataset was created by Michael Schonhardt (https://orcid.org/0000-0002-2750-1900) for the project Burchards Dekret Digital.

Creation was made possible thanks to the lemmata from Georges 1913, kindly provided via www.zeno.org by 'Henricus - Edition Deutsche Klassik GmbH'. Please consider using and supporting this valuable service.

License

CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/legalcode.en)

Citation

If you use this dataset, please cite: Michael Schonhardt, Dataset: Normalized Georges 1913, https://huggingface.co/datasets/mschonhardt/georges-1913-normalization, Doi: 10.5281/zenodo.14191142 .

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