vgaraujov/semeval-2025-task11-track-c
SemEval 2025 Task 11 - Track C Dataset This dataset contains the data for SemEval 2025 Task 11: Bridging the Gap in Text-Based Emotion Detection - Track C, organized as language-specific configurations. Dataset Description The dataset is a multi-language, multi-label emotion classification dataset with separate configurations for each language. Total languages: 30 standard ISO codes Total examples: 57254 Splits: dev, test (Track C has no train split)… See the full description on the dataset page: https://huggingface.co/datasets/vgaraujov/semeval-2025-task11-track-c.
SemEval 2025 Task 11 - Track C Dataset
This dataset contains the data for SemEval 2025 Task 11: Bridging the Gap in Text-Based Emotion Detection - Track C, organized as language-specific configurations.
Dataset Description
The dataset is a multi-language, multi-label emotion classification dataset with separate configurations for each language.
- Total languages: 30 standard ISO codes
- Total examples: 57254
- Splits: dev, test (Track C has no train split)
Track Information
Track C has more languages than Track B, but does not include a training set. It only provides dev and test splits for each language.
Language Configurations
Each language is available as a separate configuration with the following statistics:
Features
- id: Unique identifier for each example
- text: Text content to classify
- anger, disgust, fear, joy, sadness, surprise: Presence of emotion
- emotions: List of emotions present in the text
Usage
from datasets import load_dataset
# Load all data for a specific language
eng_dataset = load_dataset("YOUR_USERNAME/semeval-2025-task11-track-c", "eng")
# Or load a specific split for a language
eng_dev = load_dataset("YOUR_USERNAME/semeval-2025-task11-track-c", "eng", split="dev")Citation
If you use this dataset, please cite the following papers:
@misc{{muhammad2025brighterbridginggaphumanannotated,
title={{BRIGHTER: BRIdging the Gap in Human-Annotated Textual Emotion Recognition Datasets for 28 Languages}},
author={{Shamsuddeen Hassan Muhammad and Nedjma Ousidhoum and Idris Abdulmumin and Jan Philip Wahle and Terry Ruas and Meriem Beloucif and Christine de Kock and Nirmal Surange and Daniela Teodorescu and Ibrahim Said Ahmad and David Ifeoluwa Adelani and Alham Fikri Aji and Felermino D. M. A. Ali and Ilseyar Alimova and Vladimir Araujo and Nikolay Babakov and Naomi Baes and Ana-Maria Bucur and Andiswa Bukula and Guanqun Cao and Rodrigo Tufiño and Rendi Chevi and Chiamaka Ijeoma Chukwuneke and Alexandra Ciobotaru and Daryna Dementieva and Murja Sani Gadanya and Robert Geislinger and Bela Gipp and Oumaima Hourrane and Oana Ignat and Falalu Ibrahim Lawan and Rooweither Mabuya and Rahmad Mahendra and Vukosi Marivate and Andrew Piper and Alexander Panchenko and Charles Henrique Porto Ferreira and Vitaly Protasov and Samuel Rutunda and Manish Shrivastava and Aura Cristina Udrea and Lilian Diana Awuor Wanzare and Sophie Wu and Florian Valentin Wunderlich and Hanif Muhammad Zhafran and Tianhui Zhang and Yi Zhou and Saif M. Mohammad}},
year={{2025}},
eprint={{2502.11926}},
archivePrefix={{arXiv}},
primaryClass={{cs.CL}},
url={{https://arxiv.org/abs/2502.11926}},
}}@misc{{muhammad2025semeval2025task11bridging,
title={{SemEval-2025 Task 11: Bridging the Gap in Text-Based Emotion Detection}},
author={{Shamsuddeen Hassan Muhammad and Nedjma Ousidhoum and Idris Abdulmumin and Seid Muhie Yimam and Jan Philip Wahle and Terry Ruas and Meriem Beloucif and Christine De Kock and Tadesse Destaw Belay and Ibrahim Said Ahmad and Nirmal Surange and Daniela Teodorescu and David Ifeoluwa Adelani and Alham Fikri Aji and Felermino Ali and Vladimir Araujo and Abinew Ali Ayele and Oana Ignat and Alexander Panchenko and Yi Zhou and Saif M. Mohammad}},
year={{2025}},
eprint={{2503.07269}},
archivePrefix={{arXiv}},
primaryClass={{cs.CL}},
url={{https://arxiv.org/abs/2503.07269}},
}}License
This dataset is licensed under CC-BY 4.0.