| language: | |
| - en | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train-* | |
| - split: dev | |
| path: data/dev-* | |
| - split: test | |
| path: data/test-* | |
| - split: gen | |
| path: data/gen-* | |
| - split: train_100 | |
| path: data/train_100-* | |
| dataset_info: | |
| features: | |
| - name: input | |
| dtype: string | |
| - name: output | |
| dtype: string | |
| - name: domain | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 4363969 | |
| num_examples: 24155 | |
| - name: dev | |
| num_bytes: 549121 | |
| num_examples: 3000 | |
| - name: test | |
| num_bytes: 548111 | |
| num_examples: 3000 | |
| - name: gen | |
| num_bytes: 5721102 | |
| num_examples: 21000 | |
| - name: train_100 | |
| num_bytes: 5592847 | |
| num_examples: 39500 | |
| download_size: 5220150 | |
| dataset_size: 16775150 | |
| # Dataset Card for "COGS" | |
| It contains the dataset used in the paper [COGS: A Compositional Generalization Challenge Based on Semantic Interpretation.](https://aclanthology.org/2020.emnlp-main.731.pdf) | |
| It has four splits, where **gen** refers to the generalization split and **train_100** refers to the training version with 100 primitive exposure examples. | |
| You can use it by calling: | |
| ``` | |
| train_data = datasets.load_dataset("Punchwe/COGS", split="train") | |
| train100_data = datasets.load_dataset("Punchwe/COGS", split="train_100") | |
| gen_data = datasets.load_dataset("Punchwe/COGS", split="gen") | |
| ``` |