A Human-Annotated Dataset for Language Modeling and Named Entity Recognition in Medieval Documents

 
LINDAT / CLARIAH-CZ
  Authors
Novotný, Vít ; Luger, Kristýna ; Štefánik, Michal ; Vrabcová, Tereza and Horák, Aleš
  Item identifier
http://hdl.handle.net/11234/1-4936
 Project URL
https://starfos.tacr.cz/en/project/TL03000365
 Referenced by
https://nlp.fi.muni.cz/projects/ahisto/ner-dataset
 Date issued
2022-11-30
 Type
corpus, text
 Size
173 files, 1.58 gb
 Language(s)
Czech , English , German , Latin
 Description
This is an open dataset of sentences from 19th and 20th century letterpress reprints of documents from the Hussite era. The dataset contains a corpus for language modeling and human annotations for named entity recognition (NER).
 Publisher
Masaryk University, Brno
 Acknowledgement

TAČR

Project code: TL03000365

Project name: Accessible historical sources. Making medieval written documents available in the form of a contextual database

 

Ministerstvo školství, mládeže a tělovýchovy České republiky

Project code: LM2018101

Project name: LINDAT/CLARIAH-CZ: Digitální výzkumná infrastruktura pro jazykové technologie, umění a humanitní vědy

 Subject(s)
NER named entity recognition Medieval
 Collection(s)
LINDAT / CLARIAH-CZ Data & Tools
 
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 Files in this item

This item is
Publicly Available
and licensed under:
Public Domain Dedication (CC Zero)
Distributed under Creative Commons No Copyright
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Name
language-modeling-corpus.zip
Size
633.79 MB
Format
application/zip
Description
Sentences for unsupervised training and validation of language models
MD5
b6ed0a8e7dc263d1a1e635d6d5770f6b
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    • dataset_mlm_non-crossing_only-relevant_training.txt6 MB
    • dataset_mlm_non-crossing_all_validation.txt64 MB
    • dataset_mlm_all_only-relevant_validation.txt719 kB
    • dataset_mlm_all_only-relevant_training.txt7 MB
    • dataset_mlm_non-crossing_all_training.txt499 MB
    • dataset_mlm_all_all_validation.txt78 MB
    • dataset_mlm_non-crossing_only-relevant_validation.txt536 kB
    • dataset_mlm_all_all_training.txt601 MB
Icon
Name
named-entity-recognition-annotations.zip
Size
978.29 MB
Format
application/zip
Description
Sentences and NER tags for supervised training, validation, and testing of language models
MD5
92d80ec8d6e66263295797b1e81bd60d
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    • dataset_ner_manatee_non-crossing_only-relevant_testing_001-400.ner_tags.txt41 kB
    • dataset_ner_manatee+regests_all_only-relevant_validation_automatically_tagged.sentences.txt628 kB
    • dataset_ner_fuzzy-regex+regests_non-crossing_all_validation_automatically_tagged.ner_tags.txt10 MB
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    • dataset_ner_regests_testing.sentences.txt186 kB
    • dataset_ner_fuzzy-regex+regests_all_all_training.ner_tags.txt50 MB
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    • dataset_ner_fuzzy-regex+regests_non-crossing_only-relevant_validation_automatically_tagged.ner_tags.txt317 kB
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    • dataset_ner_manatee+regests_non-crossing_all_training.sentences.txt43 MB
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    • dataset_ner_manatee_non-crossing_only-relevant_training.ner_tags.txt546 kB
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    • dataset_ner_manatee+regests_all_all_training_automatically_tagged.sentences.txt64 MB
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    • dataset_ner_manatee+regests_all_all_training.sentences.txt64 MB
    • dataset_ner_manatee_all_all_validation.sentences.txt14 MB
    • dataset_ner_fuzzy-regex_all_only-relevant_validation_automatically_tagged.sentences.txt908 kB
    • dataset_ner_manatee+regests_non-crossing_only-relevant_training.ner_tags.txt956 kB
    • dataset_ner_fuzzy-regex_all_only-relevant_validation_automatically_tagged.ner_tags.txt394 kB
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    • dataset_ner_manatee_non-crossing_only-relevant_testing_401-500.ner_tags.txt9 kB
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    • dataset_ner_manatee_non-crossing_only-relevant_testing_401-500_automatically_tagged.docx58 kB
    • dataset_ner_fuzzy-regex_non-crossing_all_training.ner_tags.txt36 MB
    • dataset_ner_fuzzy-regex+regests_all_only-relevant_training_automatically_tagged.ner_tags.txt1 MB
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    • dataset_ner_manatee_all_only-relevant_validation_automatically_tagged.ner_tags.txt212 kB
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    • dataset_ner_fuzzy-regex_non-crossing_only-relevant_validation_automatically_tagged.ner_tags.txt266 kB
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    • dataset_ner_manatee_non-crossing_only-relevant_testing.sentences.txt343 kB
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    • dataset_ner_fuzzy-regex+regests_all_only-relevant_validation_automatically_tagged.ner_tags.txt445 kB
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    • dataset_ner_fuzzy-regex_non-crossing_only-relevant_training.ner_tags.txt897 kB
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