YAML tags: null
annotations_creators:
- expert-generated
language:
- es
language_creators:
- found
multilinguality:
- multilingual
pretty_name: MLDoc
license: cc-by-nc-4.0
size_categories: []
source_datasets: []
tags: []
task_categories:
- text-classification
task_ids: []
MLDoc
Table of Contents
- Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
Dataset Summary
For document classification, we use the Multilingual Document Classification Corpus (MLDoc) (Schwenk and Li, 2018; Lewis et al., 2004), a cross-lingual document classification dataset covering 8 languages. We use the Spanish portion to evaluate our models on monolingual classification. The corpus consists of 14,458 news articles from Reuters classified in four categories: Corporate/Industrial, Economics, Government/Social and Markets.
Supported Tasks and Leaderboards
Text Classification
Languages
The dataset is in English, German, French, Spanish, Italian, Russian, Japanese and Chinese.
Dataset Structure
Data Instances
Data Fields
Data Splits
- esp.train: 273037 lines
- esp.testa: 54837 lines (used as dev)
- esp.testb: 53049 lines (used as test)
Dataset Creation
Curation Rationale
[N/A]
Source Data
Initial Data Collection and Normalization
Who are the source language producers?
Annotations
Annotation process
Who are the annotators?
Personal and Sensitive Information
[N/A]
Considerations for Using the Data
Social Impact of Dataset
This dataset contributes to the development of language models in Spanish.
Discussion of Biases
[N/A]
Other Known Limitations
[N/A]
Additional Information
Dataset Curators
[N/A]
Licensing Information
Creative Commons Attribution Non Commercial 4.0
Citation Information
The following paper must be cited when using this corpus:
@InProceedings{SCHWENK18.658,
author = {Holger Schwenk and Xian Li},
title = {A Corpus for Multilingual Document Classification in Eight Languages},
booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)},
year = {2018},
month = {may},
date = {7-12},
location = {Miyazaki, Japan},
editor = {Nicoletta Calzolari (Conference chair) and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Hélène Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis and Takenobu Tokunaga},
publisher = {European Language Resources Association (ELRA)},
address = {Paris, France},
isbn = {979-10-95546-00-9},
language = {english}
}