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- {"kasnerz--scigen": {"description": "Scigen: dataset for reasoning-aware data-to-text generation from scientific tables.\n", "citation": "@article{moosavi:2021:SciGen,\n author = {Nafise Sadat Moosavi, Andreas R{\"u}ckl{'e}, Dan Roth, Iryna Gurevych},\n title = {Learning to Reason for Text Generation from Scientific Tables},\n journal = {arXiv preprint arXiv:2104.08296},\n year = {2021},\n url = {https://arxiv.org/abs/2104.08296}\n}\n", "homepage": "https://github.com/UKPLab/SciGen", "license": "", "features": {"paper": {"dtype": "string", "id": null, "_type": "Value"}, "paper_id": {"dtype": "string", "id": null, "_type": "Value"}, "table_caption": {"dtype": "string", "id": null, "_type": "Value"}, "table_column_names": {"dtype": "large_string", "id": null, "_type": "Value"}, "table_content_values": {"dtype": "large_string", "id": null, "_type": "Value"}, "text": {"dtype": "large_string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "scigen", "config_name": "default", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 21346753, "num_examples": 13607, "dataset_name": "scigen"}, "validation": {"name": "validation", "num_bytes": 5676434, "num_examples": 3452, "dataset_name": "scigen"}, "test": {"name": "test", "num_bytes": 808761, "num_examples": 492, "dataset_name": "scigen"}}, "download_checksums": null, "download_size": 12978477, "post_processing_size": null, "dataset_size": 27831948, "size_in_bytes": 40810425}}
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {"default": {
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+ "description": "SciGen is dataset for the task of reasoning-aware data-to-text generation consisting of tables from scientific articles and their corresponding descriptions.\n",
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+ "citation": "@article{moosavi:2021:SciGen,\n author = {Nafise Sadat Moosavi, Andreas R{\"u}ckl{'e}, Dan Roth, Iryna Gurevych},\n title = {Learning to Reason for Text Generation from Scientific Tables},\n journal = {arXiv preprint arXiv:2104.08296},\n year = {2021},\n url = {https://arxiv.org/abs/2104.08296}\n}\n",
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+ "homepage": "https://github.com/UKPLab/SciGen",
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+ "license": "CC BY-NC-SA 4.0",
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+ "features": {
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+ "paper": {
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+ "dtype": "string",
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+ "_type": "Value"
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+ },
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+ "paper_id": {
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+ "dtype": "string",
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+ "_type": "Value"
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+ },
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+ "table_caption": {
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+ "dtype": "string",
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+ "_type": "Value"
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+ },
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+ "table_column_names": {
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+ "dtype": "large_string",
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+ "_type": "Value"
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+ },
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+ "table_content_values": {
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+ "dtype": "large_string",
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+ "_type": "Value"
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+ },
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+ "text": {
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+ "dtype": "large_string",
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+ "_type": "Value"
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+ }
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+ },
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+ "builder_name": "scigen",
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+ "config_name": "default",
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+ "version": {
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+ "version_str": "1.0.0",
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+ "major": 1,
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+ "minor": 0,
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+ "patch": 0
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+ },
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+ "splits": {
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+ "train": {
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+ "name": "train",
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+ "num_bytes": 21346753,
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+ "num_examples": 13607,
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+ "dataset_name": null
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+ },
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+ "validation": {
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+ "name": "validation",
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+ "num_bytes": 5676434,
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+ "num_examples": 3452,
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+ "dataset_name": null
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+ },
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+ "test": {
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+ "name": "test",
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+ "num_bytes": 808761,
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+ "num_examples": 492,
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+ "dataset_name": null
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+ }
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+ },
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+ "download_size": 13102794,
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+ "dataset_size": 27831948,
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+ "size_in_bytes": 40934742
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+ }}