Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
json
Sub-tasks:
multi-class-classification
Languages:
English
Size:
< 1K
License:
Upload README.md
Browse files
README.md
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---
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YAML tags:
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annotations_creators:
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- auromatically-generated
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language_creators:
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- found
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language:
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- en
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license:
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- cc-by-sa-3.0
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multilinguality:
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- monolingual
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pretty_name: wikicat_ca
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size_categories:
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- unknown
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source_datasets: []
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task_categories:
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- text-classification
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task_ids:
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- multi-class-classification
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---
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# WikiCAT_es (Text Classification) English dataset
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## Dataset Description
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- **Paper:**
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- **Point of Contact:** Carlos Rodríguez-Penagos (carlos.rodriguez1@bsc.es)
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### Dataset Summary
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WikiCAT_en is a English corpus for thematic Text Classification tasks. It is created automagically from Wikipedia and Wikidata sources, and contains 28921 article summaries from the Wikiipedia classified under 19 different categories.
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This dataset was developed by BSC TeMU as part of the AINA project, and intended as an evaluation of LT capabilities to generate useful synthetic corpus.
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### Supported Tasks and Leaderboards
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Text classification, Language Model
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### Languages
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EN - English
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## Dataset Structure
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### Data Instances
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Three json files, one for each split.
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### Data Fields
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We used a simple model with the article text and associated labels, without further metadata.
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#### Example:
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<pre>
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{"version": "1.1.0",
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"data":
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[
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{
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{'sentence': 'The IEEE Donald G. Fink Prize Paper Award was established in 1979 by the board of directors of the Institute of Electrical and Electronics Engineers (IEEE) in honor of Donald G. Fink. He was a past president of the Institute of Radio Engineers (IRE), and the first general manager and executive director of the IEEE. Recipients of this award received a certificate and an honorarium. The award was presented annually since 1981 and discontinued in 2016.', 'label': 'Engineering'
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},
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.
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.
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.
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]
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}
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</pre>
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#### Labels
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'Health', 'Law', 'Entertainment', 'Religion', 'Business', 'Science', 'Engineering', 'Nature', 'Philosophy', 'Economy', 'Sports', 'Technology', 'Government', 'Mathematics', 'Military', 'Humanities', 'Music', 'Politics', 'History'
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### Data Splits
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* hftrain_es.json: 3970 label-document pairs
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* hfeval_es.json: 7909 label-document pairs
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## Dataset Creation
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### Methodology
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Se eligen páginas de partida “Category:” para representar los temas en cada lengua.
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Se extrae para cada categoría las páginas principales, así como las subcategorías, y las páginas individuales bajo estas subcategorías de primer nivel.
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Para cada página, se extrae también el “summary” que proporciona Wikipedia.
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### Curation Rationale
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### Source Data
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#### Initial Data Collection and Normalization
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The source data are Wikipedia page summaries and thematic categories
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#### Who are the source language producers?
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### Annotations
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#### Annotation process
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#### Who are the annotators?
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Automatic annotation
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### Personal and Sensitive Information
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No personal or sensitive information included.
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## Considerations for Using the Data
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### Social Impact of Dataset
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[More Information Needed]
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### Discussion of Biases
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[More Information Needed]
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### Other Known Limitations
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[More Information Needed]
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## Additional Information
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### Dataset Curators
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Carlos Rodríguez from BSC-CNS
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### Licensing Information
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This work is licensed under a <a rel="license" href="https://creativecommons.org/licenses/by-sa/4.0/">Attribution-ShareAlike 4.0 International</a>.
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### Citation Information
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```
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```
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### Funding
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This work was funded by the [Catalan Ministry of the Vice-presidency, Digital Policies and Territory](https://politiquesdigitals.gencat.cat/en/inici/index.html) within the framework of the [Aina project](https://politiquesdigitals.gencat.cat/ca/tic/aina-el-projecte-per-garantir-el-catala-en-lera-digital/).
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---
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