|
--- |
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language: |
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- afr |
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- amh |
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- arb |
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- arq |
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- ary |
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- eng |
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- es |
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- hau |
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- hin |
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- ind |
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- kin |
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- mar |
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- pan |
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- tel |
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dataset_info: |
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- config_name: afr |
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features: |
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dtype: string |
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download_size: 95864 |
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dataset_size: 131492 |
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- name: sentence1 |
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- config_name: tel |
|
features: |
|
- name: sentence1 |
|
dtype: string |
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num_examples: 130 |
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download_size: 347275 |
|
dataset_size: 771712 |
|
configs: |
|
- config_name: afr |
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data_files: |
|
- split: test |
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path: afr/test-* |
|
- split: dev |
|
path: afr/dev-* |
|
- config_name: amh |
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data_files: |
|
- split: train |
|
path: amh/train-* |
|
- split: test |
|
path: amh/test-* |
|
- split: dev |
|
path: amh/dev-* |
|
- config_name: arb |
|
data_files: |
|
- split: test |
|
path: arb/test-* |
|
- split: dev |
|
path: arb/dev-* |
|
- config_name: arq |
|
data_files: |
|
- split: train |
|
path: arq/train-* |
|
- split: test |
|
path: arq/test-* |
|
- split: dev |
|
path: arq/dev-* |
|
- config_name: ary |
|
data_files: |
|
- split: train |
|
path: ary/train-* |
|
- split: test |
|
path: ary/test-* |
|
- split: dev |
|
path: ary/dev-* |
|
- config_name: eng |
|
data_files: |
|
- split: train |
|
path: eng/train-* |
|
- split: test |
|
path: eng/test-* |
|
- split: dev |
|
path: eng/dev-* |
|
- config_name: esp |
|
data_files: |
|
- split: train |
|
path: esp/train-* |
|
- split: test |
|
path: esp/test-* |
|
- split: dev |
|
path: esp/dev-* |
|
- config_name: hau |
|
data_files: |
|
- split: train |
|
path: hau/train-* |
|
- split: test |
|
path: hau/test-* |
|
- split: dev |
|
path: hau/dev-* |
|
- config_name: hin |
|
data_files: |
|
- split: test |
|
path: hin/test-* |
|
- split: dev |
|
path: hin/dev-* |
|
- config_name: ind |
|
data_files: |
|
- split: test |
|
path: ind/test-* |
|
- split: dev |
|
path: ind/dev-* |
|
- config_name: kin |
|
data_files: |
|
- split: train |
|
path: kin/train-* |
|
- split: test |
|
path: kin/test-* |
|
- split: dev |
|
path: kin/dev-* |
|
- config_name: mar |
|
data_files: |
|
- split: train |
|
path: mar/train-* |
|
- split: test |
|
path: mar/test-* |
|
- split: dev |
|
path: mar/dev-* |
|
- config_name: pan |
|
data_files: |
|
- split: test |
|
path: pan/test-* |
|
- split: dev |
|
path: pan/dev-* |
|
- config_name: tel |
|
data_files: |
|
- split: train |
|
path: tel/train-* |
|
- split: test |
|
path: tel/test-* |
|
- split: dev |
|
path: tel/dev-* |
|
task_categories: |
|
- text-classification |
|
- sentence-similarity |
|
--- |
|
|
|
## Dataset Description |
|
|
|
- **Homepage:** https://semantic-textual-relatedness.github.io |
|
- **Repository:** [GitHub](https://github.com/semantic-textual-relatedness/Semantic_Relatedness_SemEval2024) |
|
- **Paper:** [SemRel2024: A Collection of Semantic Textual Relatedness Datasets for 14 Languages](https://arxiv.org/abs/2402.08638) |
|
- **Paper:** [SemEval Task 1: Semantic Textual Relatedness for African and Asian Languages](https://arxiv.org/pdf/2403.18933.pdf) |
|
- **Leaderboard:** https://codalab.lisn.upsaclay.fr/competitions/16799#results |
|
- **Point of Contact:** [Nedjma Ousidhoum](mailto:nedjma.ousidhoum@gmail.com) |
|
|
|
### Dataset Summary |
|
|
|
SemRel2024 is a collection of Semantic Textual Relatedness (STR) datasets for 14 languages, including African and Asian languages. The datasets are composed of sentence pairs, each assigned a relatedness score between 0 (completely) unrelated and 1 (maximally related) with a large range of expected relatedness values. |
|
SemRel2024 dataset was used as part of the SemEval2024 shared task 1. The task aims to evaluate the ability of systems to measure the semantic relatedness between two sentences. |
|
|
|
|
|
### Languages |
|
|
|
The SemRel2024 dataset covers the following 14 languages: |
|
|
|
1. Afrikaans (_afr_) |
|
2. Algerian Arabic (_arq_) |
|
3. Amharic (_amh_) |
|
4. English (_eng_) |
|
5. Hausa (_hau_) |
|
6. Indonesian (_ind_) |
|
7. Hindi (_hin_) |
|
8. Kinyarwanda (_kin_) |
|
9. Marathi (_mar_) |
|
10. Modern Standard Arabic (_arb_) |
|
11. Moroccan Arabic (_ary_) |
|
12. Punjabi (_pan_) |
|
13. Spanish (_esp_) |
|
14. Telugu (_tel_) |
|
|
|
**Note**: Spanish test labels are all -1 because the Spanish team retained the gold test labels to avoid contamination problems in future benchmarking. We refer to the [CodaLab contest website](https://codalab.lisn.upsaclay.fr/competitions/15715) to evaluate your predictions, which will remain open. |
|
|
|
## Dataset Structure |
|
|
|
### Data Instances |
|
|
|
Each instance in the dataset consists of two text segments and a relatedness score indicating the degree of semantic relatedness between them. |
|
|
|
``` |
|
{ |
|
"sentence1": "string", |
|
"sentence2": "string", |
|
"label": float |
|
} |
|
``` |
|
|
|
- sentence1: a string feature representing the first text segment. |
|
- sentence2: a string feature representing the second text segment. |
|
- label: a float value representing the semantic relatedness score between sentence1 and sentence2, typically ranging from 0 (not related at all) to 1 (highly related). |
|
|
|
|
|
## Citation Information |
|
|
|
If you use the SemRel2024 dataset in your research, please cite the following papers: |
|
|
|
``` |
|
@misc{ousidhoum2024semrel2024, |
|
title={SemRel2024: A Collection of Semantic Textual Relatedness Datasets for 14 Languages}, |
|
author={Nedjma Ousidhoum and Shamsuddeen Hassan Muhammad and Mohamed Abdalla and Idris Abdulmumin and Ibrahim Said Ahmad and |
|
Sanchit Ahuja and Alham Fikri Aji and Vladimir Araujo and Abinew Ali Ayele and Pavan Baswani and Meriem Beloucif and |
|
Chris Biemann and Sofia Bourhim and Christine De Kock and Genet Shanko Dekebo and |
|
Oumaima Hourrane and Gopichand Kanumolu and Lokesh Madasu and Samuel Rutunda and Manish Shrivastava and |
|
Thamar Solorio and Nirmal Surange and Hailegnaw Getaneh Tilaye and Krishnapriya Vishnubhotla and Genta Winata and |
|
Seid Muhie Yimam and Saif M. Mohammad}, |
|
year={2024}, |
|
eprint={2402.08638}, |
|
archivePrefix={arXiv}, |
|
primaryClass={cs.CL} |
|
} |
|
``` |
|
|
|
``` |
|
@inproceedings{ousidhoum-etal-2024-semeval, |
|
title = "{S}em{E}val-2024 Task 1: Semantic Textual Relatedness for African and Asian Languages", |
|
author = "Ousidhoum, Nedjma and Muhammad, Shamsuddeen Hassan and Abdalla, Mohamed and Abdulmumin, Idris and |
|
Ahmad,Ibrahim Said and Ahuja, Sanchit and Aji, Alham Fikri and Araujo, Vladimir and Beloucif, Meriem and |
|
De Kock, Christine and Hourrane, Oumaima and Shrivastava, Manish and Solorio, Thamar and Surange, Nirmal and |
|
Vishnubhotla, Krishnapriya and Yimam, Seid Muhie and Mohammad, Saif M.", |
|
booktitle = "Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)", |
|
year = "2024", |
|
publisher = "Association for Computational Linguistics" |
|
} |
|
|
|
``` |
|
|