--- 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-* 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 --- # 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 ```python 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.