Dataset:
metrec

Task Categories: text-classification
Languages: ar
Multilinguality: monolingual
Size Categories: 10K<n<100K
Licenses: unknown
Language Creators: found
Annotations Creators: no-annotation
Source Datasets: original

Dataset Card for MetRec

Dataset Summary

The dataset contains the verses and their corresponding meter classes. Meter classes are represented as numbers from 0 to 13. The dataset can be highly useful for further research in order to improve the field of Arabic poems’ meter classification. The train dataset contains 47,124 records and the test dataset contains 8,316 records.

Supported Tasks and Leaderboards

The dataset was published on this paper. A benchmark is acheived on this paper.

Languages

The dataset is based on Arabic.

Dataset Structure

Data Instances

A typical data point comprises a label which is out of 13 classes and a verse part of poem.

Data Fields

[N/A]

Data Splits

The data is split into a training and testing. The split is organized as the following

Tain Test
data split 47,124 8,316

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

[More Information Needed]

Initial Data Collection and Normalization

The dataset was collected from Aldiwan.

Who are the source language producers?

The poems are from different poets.

Annotations

The dataset does not contain any additional annotations.

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Discussion of Social Impact and Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

[More Information Needed]

Citation Information

[More Information Needed]

@article{metrec2020,
  title={MetRec: A dataset for meter classification of arabic poetry},
  author={Al-shaibani, Maged S and Alyafeai, Zaid and Ahmad, Irfan},
  journal={Data in Brief},
  year={2020},
  publisher={Elsevier}
}

Contributions

Thanks to @zaidalyafeai for adding this dataset.

Models trained or fine-tuned on metrec

None yet