Datasets:
Tasks:
Token Classification
Size Categories:
1K<n<10K
Language Creators:
machine-generated
ArXiv:
Tags:
License:
| license: cc-by-sa-4.0 | |
| language_creators: | |
| - machine-generated | |
| dataset_info: | |
| features: | |
| - name: tokens_a | |
| sequence: string | |
| - name: tokens_b | |
| sequence: string | |
| - name: labels_a | |
| sequence: float64 | |
| - name: labels_b | |
| sequence: float64 | |
| - name: lang_a | |
| dtype: string | |
| - name: lang_b | |
| dtype: string | |
| - name: subset | |
| dtype: string | |
| - name: id | |
| dtype: string | |
| - name: alignments | |
| dtype: string | |
| splits: | |
| - name: train_en | |
| num_bytes: 1640900 | |
| num_examples: 1506 | |
| - name: train_de | |
| num_bytes: 1101404 | |
| num_examples: 3012 | |
| - name: train_es | |
| num_bytes: 1154765 | |
| num_examples: 3012 | |
| - name: train_fr | |
| num_bytes: 1206414 | |
| num_examples: 3012 | |
| - name: train_ja | |
| num_bytes: 838252 | |
| num_examples: 3012 | |
| - name: train_ko | |
| num_bytes: 829328 | |
| num_examples: 3012 | |
| - name: train_zh | |
| num_bytes: 796140 | |
| num_examples: 3012 | |
| - name: test_en | |
| num_bytes: 833900 | |
| num_examples: 750 | |
| - name: test_de | |
| num_bytes: 558624 | |
| num_examples: 1500 | |
| - name: test_es | |
| num_bytes: 580224 | |
| num_examples: 1500 | |
| - name: test_fr | |
| num_bytes: 610017 | |
| num_examples: 1500 | |
| - name: test_ja | |
| num_bytes: 425912 | |
| num_examples: 1500 | |
| - name: test_ko | |
| num_bytes: 424407 | |
| num_examples: 1500 | |
| - name: test_zh | |
| num_bytes: 403680 | |
| num_examples: 1500 | |
| download_size: 2569205 | |
| dataset_size: 11403967 | |
| task_categories: | |
| - token-classification | |
| language: | |
| - en | |
| - de | |
| - es | |
| - fr | |
| - ja | |
| - ko | |
| - zh | |
| size_categories: | |
| - 1K<n<10K | |
| Training and test data for the task of Recognizing Semantic Differences (RSD). | |
| [See the paper](https://arxiv.org/abs/2305.13303) for details on how the dataset was created, and see our code at https://github.com/ZurichNLP/recognizing-semantic-differences for an example of how to use the data for evaluation. | |
| The data are derived from the [SemEval-2016 Task 2 for Interpretable Semantic Textual Similarity](https://alt.qcri.org/semeval2016/task2/) organized by [Agirre et al. (2016)](http://dx.doi.org/10.18653/v1/S16-1082). | |
| The original URLs of the data are: | |
| * Train: http://alt.qcri.org/semeval2016/task2/data/uploads/train_2015_10_22.utf-8.tar.gz | |
| * Test: http://alt.qcri.org/semeval2016/task2/data/uploads/test_goldstandard.tar.gz | |
| The translations into non-English languages have been created using machine translation (DeepL). | |
| ## Citation | |
| ```bibtex | |
| @inproceedings{vamvas-sennrich-2023-rsd, | |
| title={Towards Unsupervised Recognition of Token-level Semantic Differences in Related Documents}, | |
| author={Jannis Vamvas and Rico Sennrich}, | |
| month = dec, | |
| year = "2023", | |
| booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing", | |
| address = "Singapore", | |
| publisher = "Association for Computational Linguistics", | |
| } | |
| ``` | |