Datasets:
Tasks:
Token Classification
Sub-tasks:
named-entity-recognition
Languages:
Arabic
Multilinguality:
monolingual
Size Categories:
100K<n<1M
Language Creators:
expert-generated
Annotations Creators:
expert-generated
Source Datasets:
original
Tags:
License:
File size: 4,508 Bytes
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---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- ar
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
pretty_name: CANER
dataset_info:
features:
- name: token
dtype: string
- name: ner_tag
dtype:
class_label:
names:
'0': Allah
'1': Book
'2': Clan
'3': Crime
'4': Date
'5': Day
'6': Hell
'7': Loc
'8': Meas
'9': Mon
'10': Month
'11': NatOb
'12': Number
'13': O
'14': Org
'15': Para
'16': Pers
'17': Prophet
'18': Rlig
'19': Sect
'20': Time
splits:
- name: train
num_bytes: 5095617
num_examples: 258240
download_size: 1459014
dataset_size: 5095617
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for CANER
## 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
- **Homepage:**
- **Repository:** [Classical-Arabic-Named-Entity-Recognition-Corpus](https://github.com/RamziSalah)
- **Paper:** [Researchgate](https://www.researchgate.net/publication/330075080_BUILDING_THE_CLASSICAL_ARABIC_NAMED_ENTITY_RECOGNITION_CORPUS_CANERCORPUS)
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
The Classical Arabic Named Entity Recognition corpus is a new corpus of tagged data that can be useful for handling the issues in recognition of Arabic named entities.
### Supported Tasks and Leaderboards
- Named Entity Recognition
### Languages
Classical Arabic
## Dataset Structure
### Data Instances
An example from the dataset:
```
{'ner_tag': 1, 'token': 'الجامع'}
```
Where 1 stands for "Book"
### Data Fields
- `id`: id of the sample
- `token`: the tokens of the example text
- `ner_tag`: the NER tags of each token
The NER tags correspond to this list:
```
"Allah",
"Book",
"Clan",
"Crime",
"Date",
"Day",
"Hell",
"Loc",
"Meas",
"Mon",
"Month",
"NatOb",
"Number",
"O",
"Org",
"Para",
"Pers",
"Prophet",
"Rlig",
"Sect",
"Time"
```
### Data Splits
Training splits only
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
Ramzi Salah and Lailatul Qadri Zakaria
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
[More Information Needed]
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
@article{article,
author = {Salah, Ramzi and Zakaria, Lailatul},
year = {2018},
month = {12},
pages = {},
title = {BUILDING THE CLASSICAL ARABIC NAMED ENTITY RECOGNITION CORPUS (CANERCORPUS)},
volume = {96},
journal = {Journal of Theoretical and Applied Information Technology}
}
### Contributions
Thanks to [@KMFODA](https://github.com/KMFODA) for adding this dataset. |