Datasets:
Tasks:
Token Classification
Modalities:
Text
Formats:
parquet
Languages:
Arabic
Size:
100K - 1M
Tags:
Named Entity Recognition
License:
File size: 1,200 Bytes
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---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: word
dtype: string
- name: tag
dtype: string
splits:
- name: train
num_bytes: 2286358
num_examples: 125102
- name: test
num_bytes: 460049
num_examples: 25008
download_size: 1029992
dataset_size: 2746407
license: cc-by-sa-4.0
language:
- ar
tags:
- Named Entity Recognition
task_categories:
- token-classification
size_categories:
- 100K<n<1M
---
# Dataset Card for "ANERCorp"
## Papers:
Benajiba, Yassine, Paolo Rosso, and José Miguel Benedí Ruiz. "Anersys: An Arabic named entity recognition system based on maximum entropy." In International Conference on Intelligent Text Processing and Computational Linguistics, pp. 143-153. Springer, Berlin, Heidelberg, 2007.
Ossama Obeid, Nasser Zalmout, Salam Khalifa, Dima Taji, Mai Oudah, Bashar Alhafni, Go Inoue, Fadhl Eryani, Alexander Erdmann, and Nizar Habash. "CAMeL Tools: An Open Source Python Toolkit, for Arabic Natural Language Processing." In Proceedings of the Conference on Language Resources and Evaluation (LREC 2020), Marseille, 2020. |