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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 Models (CNEC) for NameTag
- Creator:
- Straka, Milan and Straková, Jana
- Publisher:
- Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
- Type:
- text, languageDescription, and mlmodel
- Subject:
- NameTag, Czech, and named entity recognition
- Language:
- Czech
- Description:
- Czech models for NameTag, providing recognition of named entities. The models are trained on Czech Named Entity Corpus 2.0 and 1.1. and This work has been using language resources developed and/or stored and/or distributed by the LINDAT/CLARIN project of the Ministry of Education of the Czech Republic (project LM2010013). Czech models are trained on Czech Named Entity Corpus, which was created by Magda Ševčíková, Zdeněk Žabokrtský, Jana Straková and Milan Straka. The recognizer research was supported by the projects MSM0021620838 and LC536 of Ministry of Education, Youth and Sports of the Czech Republic, 1ET101120503 of Academy of Sciences of the Czech Republic, LINDAT/CLARIN project of the Ministry of Education of the Czech Republic (project LM2010013), and partially by SVV project number 267 314. The research was performed by Jana Straková, Zdeněk Žabokrtský and Milan Straka. Czech models use MorphoDiTa as a tagger and lemmatizer, therefore MorphoDiTa Acknowledgements (http://ufal.mff.cuni.cz/morphodita#morphodita_acknowledgements) and Czech MorphoDiTa Model Acknowledgements (http://ufal.mff.cuni.cz/morphodita/users-manual#czech-morfflex-pdt_acknowledgements) apply.
- 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. Czech Named Entity Corpus 1.1
- Creator:
- Ševčíková, Magda, Žabokrtský, Zdeněk, Straková, Jana, and Straka, Milan
- Publisher:
- Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
- Type:
- text and corpus
- Subject:
- named entity recognition and corpus
- Language:
- Czech
- Description:
- Czech Named Entity Corpus 1.1 fixes some issues of the Czech Named Entity Corpus 1.0: misannotated entities are fixed, all formats contain the same data, tmt format is replaced with treex format, all formats contain splitting into training, development and testing portion of the data. and SVV 267 314 (Teoretické základy informatiky a výpočetní lingvistiky), LM2010013 (LINDAT-CLARIN: Institut pro analýzu, zpracování a distribuci lingvistických dat), GPP406/12/P175 (Vybrané derivační vztahy pro automatické zpracování češtiny), PRVOUK (PRVOUK)
- Rights:
- Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0), http://creativecommons.org/licenses/by-nc-sa/3.0/, and PUB
5. Czech Named Entity Corpus 2.0
- Creator:
- Ševčíková, Magda, Žabokrtský, Zdeněk, Straková, Jana, and Straka, Milan
- Publisher:
- Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
- Type:
- text and corpus
- Subject:
- named entity recognition
- Language:
- Czech
- Description:
- Czech Named Entity Corpus 2.0 is a corpus of 8993 Czech sentences with manually annotated 35220 Czech named entities, classified according to a two-level hierarchy of 46 named entities. and SVV 267 314 (Teoretické základy informatiky a výpočetní lingvistiky), LM2010013 (LINDAT-CLARIN: Institut pro analýzu, zpracování a distribuci lingvistických dat), GPP406/12/P175 (Vybrané derivační vztahy pro automatické zpracování češtiny), PRVOUK (PRVOUK)
- Rights:
- Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0), http://creativecommons.org/licenses/by-nc-sa/3.0/, and PUB
6. NameTag 2 Models (2020-08-31)
- 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
- 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
7. 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
8. NameTag service description
- Creator:
- Straková, Jana and Straka, Milan
- Publisher:
- Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
- Type:
- service and toolService
- Subject:
- named entity recognition, NameTag, and WeblichtXML
- Language:
- Czech, German, English, Spanish, and Dutch
- Description:
- Metadata description of nametag (http://hdl.handle.net/11234/1-3633, https://lindat.mff.cuni.cz/services/nametag/) provided for weblicht.
- Rights:
- Not specified
9. Parallel Global Voices, Czech-English NER+NEL
- Creator:
- Nevěřilová, Zuzana and Žižková, Hana
- Publisher:
- Masaryk University, Brno
- Type:
- text, other, and lexicalConceptualResource
- Subject:
- named entity recognition, named entities, named entity, named entitity corpus, named entity linking, named entity disambiguation, and wikidata
- Language:
- English and Czech
- Description:
- Annotation of named entities to the existing source Parallel Global Voices, ces-eng language pair. The named entity annotations distinguish four classes: Person, Organization, Location, Misc. The annotation is in the IOB schema (annotation per token, beginning + inside of the multi-word annotation). NEL annotation contains Wikidata Qnames.
- Rights:
- Creative Commons - Attribution 4.0 International (CC BY 4.0), http://creativecommons.org/licenses/by/4.0/, and PUB
10. SumeCzech-NER
- Creator:
- Marek, Petr and Müller, Štěpán
- Publisher:
- Czech Technical University in Prague
- Type:
- text and corpus
- Subject:
- SumeCzech, named entity recognition, named entitity corpus, and summarization
- Language:
- Czech
- Description:
- SumeCzech-NER SumeCzech-NER contains named entity annotations of SumeCzech 1.0 (Straka et al. 2018, SumeCzech: Large Czech News-Based Summarization Dataset). Format The dataset is split into four files. Files are in jsonl format. There is one JSON object on each line of the file. The most important fields of JSON objects are: - dataset: train, dev, test, oodtest - ne_abstract: list of named entity annotations of article's abstract - ne_headline: list of named entity annotations of article's headline - ne_text: list of name entity annotations of article's text - url: article's URL that can be used to match article across SumeCzech and SumeCzech-NER Annotations We used SpaCy's NER model trained on CoNLL-based extended CNEC 2.0. The model achieved a 78.45 F-Score on the dataset's testing set. The annotations are in IOB2 format. The entity types are: Numbers in addresses, Geographical names, Institutions, Media names, Artifact names, Personal names, and Time expressions. Tokenization We used the following Python code for tokenization: from typing import List from nltk.tokenize import word_tokenize def tokenize(text: str) -> List[str]: for mark in ('.', ',', '?', '!', '-', '–', '/'): text = text.replace(mark, f' {mark} ') tokens = word_tokenize(text) return tokens
- Rights:
- Mozilla Public License 2.0, http://opensource.org/licenses/MPL-2.0, and PUB