| | --- |
| | 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: train_it |
| | num_bytes: 1111516 |
| | 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 |
| | - name: test_it |
| | num_bytes: 561989 |
| | num_examples: 1500 |
| | download_size: 2569205 |
| | dataset_size: 11403967 |
| | task_categories: |
| | - token-classification |
| | language: |
| | - en |
| | - de |
| | - es |
| | - fr |
| | - ja |
| | - ko |
| | - zh |
| | - it |
| | 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", |
| | } |
| | ``` |
| |
|
