Datasets:
Tasks:
Token Classification
Formats:
csv
Sub-tasks:
named-entity-recognition
Languages:
Quechua
Size:
10K<n<100K
Tags:
License:
File size: 2,018 Bytes
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---
annotations_creators:
- crowdsourced
language:
- qu
license:
- apache-2.0
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
---
# Dataset Card for WikiANN
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Paper:** The original datasets come from Introducing QuBERT: A Large Monolingual Corpus and BERT Model for
Southern Quechua [paper](https://aclanthology.org/2022.deeplo-1.1.pdf) by Rodolfo Zevallos et al. (2022).
- **Point of Contact:** [Rodolfo Zevallos](mailto:rodolfojoel.zevallos@upf.edu)
### Dataset Summary
NER_Quechua_IIC is a named entity recognition dataset consisting of dictionary texts provided by the Peruvian Ministry of Education, annotated with LOC (location), PER (person) and ORG (organization) tags in the IOB2 format.
### Supported Tasks and Leaderboards
- `named-entity-recognition`: The dataset can be used to train a model for named entity recognition in Quechua languages.
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