Datasets:
Dataset Card for REBEL-Portuguese
Table of Contents
- Dataset Card for REBEL-Portuguese
Dataset Description
- Repository: https://github.com/Babelscape/rebel
- Paper: https://github.com/Babelscape/rebel/blob/main/docs/EMNLP_2021_REBEL__Camera_Ready_.pdf
- Point of Contact: julianarsg13@gmail.com
Dataset Summary
Dataset adapted to Portuguese from REBEL-dataset .
Supported Tasks and Leaderboards
text-retrieval-other-relation-extraction
: The dataset can be used to train a model for Relation Extraction, which consists in extracting triplets from raw text, made of subject, object and relation type. Success on this task is typically measured by achieving a high F1. The BART) model currently achieves the following score: 74 Micro F1 and 51 Macro F1 for the 220 most frequent relation types.
Languages
The dataset is in Portuguese, from the Portuguese Wikipedia.
Dataset Structure
Data Instances
Data Fields
Data Splits
Dataset Creation
Curation Rationale
Source Data
Data comes from Wikipedia text before the table of contents, as well as Wikidata for the triplets annotation.
Initial Data Collection and Normalization
For the data collection, the dataset extraction pipeline cRocoDiLe: Automatic Relation Extraction Dataset with NLI filtering insipired by T-REx Pipeline more details found at: T-REx Website. The starting point is a Wikipedia dump as well as a Wikidata one. After the triplets are extracted, an NLI system was used to filter out those not entailed by the text.
Who are the source language producers?
Any Wikipedia and Wikidata contributor.
Annotations
Annotation process
The dataset extraction pipeline cRocoDiLe: Automatic Relation Extraction Dataset with NLI filtering.
Who are the annotators?
Automatic annottations
Personal and Sensitive Information
All text is from Wikipedia, any Personal or Sensitive Information there may be present in this dataset.
Considerations for Using the Data
Social Impact of Dataset
Discussion of Biases
Other Known Limitations
Not for now
Additional Information
Dataset Curators
Licensing Information
Citation Information
Contributions
Thanks to @ju-resplande for adding this dataset.