metadata
language:
- af
- am
- ar
- de
- en
- es
- ha
- hi
- ig
- mr
- om
- pcm
- pt
- ro
- ru
- rw
- so
- su
- sv
- sw
- ti
- tt
- uk
- vmw
- yo
- zh
license: cc-by-4.0
configs:
- config_name: afr
data_files:
- split: train
path: afr/train-*
- split: dev
path: afr/dev-*
- split: test
path: afr/test-*
- config_name: amh
data_files:
- split: train
path: amh/train-*
- split: dev
path: amh/dev-*
- split: test
path: amh/test-*
- config_name: arq
data_files:
- split: train
path: arq/train-*
- split: dev
path: arq/dev-*
- split: test
path: arq/test-*
- config_name: ary
data_files:
- split: train
path: ary/train-*
- split: dev
path: ary/dev-*
- split: test
path: ary/test-*
- config_name: chn
data_files:
- split: train
path: chn/train-*
- split: dev
path: chn/dev-*
- split: test
path: chn/test-*
- config_name: deu
data_files:
- split: train
path: deu/train-*
- split: dev
path: deu/dev-*
- split: test
path: deu/test-*
- config_name: eng
data_files:
- split: train
path: eng/train-*
- split: dev
path: eng/dev-*
- split: test
path: eng/test-*
- config_name: esp
data_files:
- split: train
path: esp/train-*
- split: dev
path: esp/dev-*
- split: test
path: esp/test-*
dataset_info:
- config_name: afr
features:
- name: id
dtype: string
- name: text
dtype: string
- name: anger
dtype: int64
- name: disgust
dtype: int64
- name: fear
dtype: int64
- name: joy
dtype: int64
- name: sadness
dtype: int64
- name: surprise
dtype: int64
- name: emotions
sequence: string
splits:
- name: train
num_bytes: 278319.3696273311
num_examples: 1222
- name: dev
num_bytes: 22020.44791911592
num_examples: 98
- name: test
num_bytes: 240367.97557453977
num_examples: 1065
download_size: 181733
dataset_size: 540707.7931209868
- config_name: amh
features:
- name: id
dtype: string
- name: text
dtype: string
- name: anger
dtype: int64
- name: disgust
dtype: int64
- name: fear
dtype: int64
- name: joy
dtype: int64
- name: sadness
dtype: int64
- name: surprise
dtype: int64
- name: emotions
sequence: string
splits:
- name: train
num_bytes: 808310.5096623552
num_examples: 3549
- name: dev
num_bytes: 133021.4813073125
num_examples: 592
- name: test
num_bytes: 400387.5949945855
num_examples: 1774
download_size: 899161
dataset_size: 1341719.5859642532
- config_name: arq
features:
- name: id
dtype: string
- name: text
dtype: string
- name: anger
dtype: int64
- name: disgust
dtype: int64
- name: fear
dtype: int64
- name: joy
dtype: int64
- name: sadness
dtype: int64
- name: surprise
dtype: int64
- name: emotions
sequence: string
splits:
- name: train
num_bytes: 205209.289717042
num_examples: 901
- name: dev
num_bytes: 22469.844815424407
num_examples: 100
- name: test
num_bytes: 203579.26194200458
num_examples: 902
download_size: 171526
dataset_size: 431258.39647447097
- config_name: ary
features:
- name: id
dtype: string
- name: text
dtype: string
- name: anger
dtype: int64
- name: disgust
dtype: int64
- name: fear
dtype: int64
- name: joy
dtype: int64
- name: sadness
dtype: int64
- name: surprise
dtype: int64
- name: emotions
sequence: string
splits:
- name: train
num_bytes: 366233.67132630805
num_examples: 1608
- name: dev
num_bytes: 59994.48565718316
num_examples: 267
- name: test
num_bytes: 183266.4752737336
num_examples: 812
download_size: 260965
dataset_size: 609494.6322572248
- config_name: chn
features:
- name: id
dtype: string
- name: text
dtype: string
- name: anger
dtype: int64
- name: disgust
dtype: int64
- name: fear
dtype: int64
- name: joy
dtype: int64
- name: sadness
dtype: int64
- name: surprise
dtype: int64
- name: emotions
sequence: string
splits:
- name: train
num_bytes: 601734.6763955882
num_examples: 2642
- name: dev
num_bytes: 44939.689630848814
num_examples: 200
- name: test
num_bytes: 596293.1375285765
num_examples: 2642
download_size: 781783
dataset_size: 1242967.5035550136
- config_name: deu
features:
- name: id
dtype: string
- name: text
dtype: string
- name: anger
dtype: int64
- name: disgust
dtype: int64
- name: fear
dtype: int64
- name: joy
dtype: int64
- name: sadness
dtype: int64
- name: surprise
dtype: int64
- name: emotions
sequence: string
splits:
- name: train
num_bytes: 592852.1433223755
num_examples: 2603
- name: dev
num_bytes: 44939.689630848814
num_examples: 200
- name: test
num_bytes: 587716.6276019732
num_examples: 2604
download_size: 885858
dataset_size: 1225508.4605551977
- config_name: eng
features:
- name: id
dtype: string
- name: text
dtype: string
- name: anger
dtype: int64
- name: disgust
dtype: int64
- name: fear
dtype: int64
- name: joy
dtype: int64
- name: sadness
dtype: int64
- name: surprise
dtype: int64
- name: emotions
sequence: string
splits:
- name: train
num_bytes: 630432.0909398139
num_examples: 2768
- name: dev
num_bytes: 26065.01998589231
num_examples: 116
- name: test
num_bytes: 624505.3412345084
num_examples: 2767
download_size: 384400
dataset_size: 1281002.4521602145
- config_name: esp
features:
- name: id
dtype: string
- name: text
dtype: string
- name: anger
dtype: int64
- name: disgust
dtype: int64
- name: fear
dtype: int64
- name: joy
dtype: int64
- name: sadness
dtype: int64
- name: surprise
dtype: int64
- name: emotions
sequence: string
splits:
- name: train
num_bytes: 454603.48754185997
num_examples: 1996
- name: dev
num_bytes: 41344.51446038091
num_examples: 184
- name: test
num_bytes: 382557.4822524365
num_examples: 1695
download_size: 204003
dataset_size: 878505.4842546773
SemEval 2025 Task 11 - Track A Dataset
This dataset contains the data for SemEval 2025 Task 11: Bridging the Gap in Text-Based Emotion Detection - Track A, 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: 26 standard ISO codes
- Total examples: 115159
- Splits: train, dev, test
Language Configurations
Each language is available as a separate configuration with the following statistics:
| ISO Code | Original Code(s) | Train Examples | Dev Examples | Test Examples | Total |
|---|---|---|---|---|---|
| af | afr | 1222 | 98 | 1065 | 2385 |
| am | amh | 3549 | 592 | 1774 | 5915 |
| ar | arq, ary | 2509 | 367 | 1714 | 4590 |
| de | deu | 2603 | 200 | 2604 | 5407 |
| en | eng | 2768 | 116 | 2767 | 5651 |
| es | esp | 1996 | 184 | 1695 | 3875 |
| ha | hau | 2145 | 356 | 1080 | 3581 |
| hi | hin | 2556 | 100 | 1010 | 3666 |
| ig | ibo | 2880 | 479 | 1444 | 4803 |
| mr | mar | 2415 | 100 | 1000 | 3515 |
| om | orm | 3442 | 574 | 1721 | 5737 |
| pcm | pcm | 3728 | 620 | 1870 | 6218 |
| pt | ptbr, ptmz | 3772 | 457 | 3002 | 7231 |
| ro | ron | 1241 | 123 | 1119 | 2483 |
| ru | rus | 2679 | 199 | 1000 | 3878 |
| rw | kin | 2451 | 407 | 1231 | 4089 |
| so | som | 3392 | 566 | 1696 | 5654 |
| su | sun | 924 | 199 | 926 | 2049 |
| sv | swe | 1187 | 200 | 1188 | 2575 |
| sw | swa | 3307 | 551 | 1656 | 5514 |
| ti | tir | 3681 | 614 | 1840 | 6135 |
| tt | tat | 1000 | 200 | 1000 | 2200 |
| uk | ukr | 2466 | 249 | 2234 | 4949 |
| vmw | vmw | 1551 | 258 | 777 | 2586 |
| yo | yor | 2992 | 497 | 1500 | 4989 |
| zh | chn | 2642 | 200 | 2642 | 5484 |
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-a", "eng")
# Or load a specific split for a language
eng_train = load_dataset("YOUR_USERNAME/semeval-2025-task11-track-a", "eng", split="train")
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.