| --- |
| dataset_info: |
| features: |
| - name: sentence1 |
| dtype: string |
| - name: sentence2 |
| dtype: string |
| - name: gold_label |
| dtype: string |
| - name: genre |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 532705 |
| num_examples: 4068 |
| download_size: 146614 |
| dataset_size: 532705 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| license: cc-by-sa-4.0 |
| task_categories: |
| - text-classification |
| language: |
| - en |
| --- |
| # Dataset Card for "med" |
|
|
| Crowsourced (=original part) of the MED dataset for Monotonicity Entailment |
| https://github.com/verypluming/MED |
| ``` |
| @inproceedings{yanaka-etal-2019-neural, |
| title = "Can Neural Networks Understand Monotonicity Reasoning?", |
| author = "Yanaka, Hitomi and |
| Mineshima, Koji and |
| Bekki, Daisuke and |
| Inui, Kentaro and |
| Sekine, Satoshi and |
| Abzianidze, Lasha and |
| Bos, Johan", |
| booktitle = "Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP", |
| year = "2019", |
| pages = "31--40", |
| } |
| ``` |
