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2. A Human-Annotated Dataset for Language Modeling and Named Entity Recognition in Medieval Documents (2023-01-05)
- Creator:
- Novotný, Vít, Luger, Kristýna, Štefánik, Michal, Vrabcová, Tereza, and Horák, Aleš
- Publisher:
- Masaryk University, Brno
- Type:
- text and corpus
- Subject:
- NER, named entity recognition, and Medieval
- Language:
- Czech, English, German, and 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).
- Rights:
- Public Domain Dedication (CC Zero), http://creativecommons.org/publicdomain/zero/1.0/, and PUB
3. Czech Named Entity Corpus 1.0
- Creator:
- Ševčíková, Magda, Žabokrtský, Zdeněk, and Straková, Jana
- Publisher:
- Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
- Type:
- text and corpus
- Subject:
- named entity recognition, named entitity corpus, Czech, NER, and corpus
- Language:
- Czech
- Description:
- The presented Czech Named Entity Corpus 1.0 is the first publicly available corpus providing a large body of manually annotated named entities in Czech sentences, including a fine-grained classification. and 1ET101120503 (Integrace jazykových zdrojů za účelem extrakce informací z přirozených textů)
- Rights:
- Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0), http://creativecommons.org/licenses/by-nc-sa/3.0/, and PUB
4. DaMuEL 1.0: A Large Multilingual Dataset for Entity Linking
- Creator:
- Kubeša, David and Straka, Milan
- Publisher:
- Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
- Type:
- text and corpus
- Subject:
- entity linking, NEL, NER, dataset, and knowledge base
- Language:
- Afrikaans, Arabic, Armenian, Basque, Belarusian, Bulgarian, Catalan, Chinese, Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, Galician, German, Hebrew, Hindi, Hungarian, Indonesian, Irish, Italian, Japanese, Korean, Latin, Latvian, Lithuanian, Maltese, Marathi, Modern Greek (1453-), Northern Sami, Norwegian Nynorsk, Persian, Polish, Portuguese, Romanian, Russian, Scottish Gaelic, Serbian, Slovak, Slovenian, Spanish, Swedish, Tamil, Telugu, Uighur, Ukrainian, Urdu, Vietnamese, and Wolof
- Description:
- We present DaMuEL, a large Multilingual Dataset for Entity Linking containing data in 53 languages. DaMuEL consists of two components: a knowledge base that contains language-agnostic information about entities, including their claims from Wikidata and named entity types (PER, ORG, LOC, EVENT, BRAND, WORK_OF_ART, MANUFACTURED); and Wikipedia texts with entity mentions linked to the knowledge base, along with language-specific text from Wikidata such as labels, aliases, and descriptions, stored separately for each language. The Wikidata QID is used as a persistent, language-agnostic identifier, enabling the combination of the knowledge base with language-specific texts and information for each entity. Wikipedia documents deliberately annotate only a single mention for every entity present; we further automatically detect all mentions of named entities linked from each document. The dataset contains 27.9M named entities in the knowledge base and 12.3G tokens from Wikipedia texts. The dataset is published under the CC BY-SA licence.
- Rights:
- Creative Commons - Attribution-ShareAlike 4.0 International (CC BY-SA 4.0), http://creativecommons.org/licenses/by-sa/4.0/, and PUB
5. NameTag 2 Models (2021-09-16)
- Creator:
- Straková, Jana and Straka, Milan
- Publisher:
- Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
- Type:
- text, mlmodel, and languageDescription
- Subject:
- named entity recognition and NER
- Language:
- English, German, Dutch, Spanish, and Czech
- Description:
- NER models for NameTag 2, named entity recognition tool, for English, German, Dutch, Spanish and Czech. Model documentation including performance can be found here: https://ufal.mff.cuni.cz/nametag/2/models . These models are for NameTag 2, named entity recognition tool, which can be found here: https://ufal.mff.cuni.cz/nametag/2 .
- Rights:
- Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB
6. NameTag 3 Czech CNEC 2.0 Model
- Creator:
- Straková, Jana
- Publisher:
- Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
- Type:
- text, mlmodel, and languageDescription
- Subject:
- named entity recognition, NER, NameTag, and Czech
- Language:
- Czech
- Description:
- This is a trained model for the supervised machine learning tool NameTag 3 (https://ufal.mff.cuni.cz/nametag/3/), trained on the Czech Named Entity Corpus 2.0 (https://ufal.mff.cuni.cz/cnec/cnec2.0). NameTag 3 is an open-source tool for both flat and nested named entity recognition (NER). NameTag 3 identifies proper names in text and classifies them into a set of predefined categories, such as names of persons, locations, organizations, etc. The model documentation can be found at https://ufal.mff.cuni.cz/nametag/3/models#czech-cnec2.
- Rights:
- Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB
7. NameTag 3 Multilingual CoNLL Model
- Creator:
- Straková, Jana
- Publisher:
- Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
- Type:
- text, mlmodel, and languageDescription
- Subject:
- named entity recognition, NER, NameTag, and multilingual
- Language:
- English, German, Dutch, Spanish, Ukrainian, and Czech
- Description:
- This is a trained model for the supervised machine learning tool NameTag 3 (https://ufal.mff.cuni.cz/nametag/3/), trained jointly on several NE corpora: English CoNLL-2003, German CoNLL-2003, Dutch CoNLL-2002, Spanish CoNLL-2002, Ukrainian Lang-uk, and Czech CNEC 2.0, all harmonized to flat NEs with 4 labels PER, ORG, LOC, and MISC. NameTag 3 is an open-source tool for both flat and nested named entity recognition (NER). NameTag 3 identifies proper names in text and classifies them into a set of predefined categories, such as names of persons, locations, organizations, etc. The model documentation can be found at https://ufal.mff.cuni.cz/nametag/3/models#multilingual-conll.
- Rights:
- Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB