Datasets:
Convert dataset to Parquet
Browse filesConvert dataset to Parquet.
- README.md +31 -0
- dataset_infos.json +455 -1
- en/test-00000-of-00001.parquet +3 -0
- en/train-00000-of-00001.parquet +3 -0
- en/validation-00000-of-00001.parquet +3 -0
README.md
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@@ -3,6 +3,37 @@ language:
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- de
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- en
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- ja
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---
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# Amazon Multilingual Counterfactual Dataset
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- de
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- en
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- ja
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dataset_info:
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config_name: en
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features:
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- name: text
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dtype: string
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- name: label
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dtype: int32
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- name: label_text
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dtype: string
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splits:
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- name: train
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num_bytes: 548743
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num_examples: 4018
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- name: validation
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num_bytes: 46405
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num_examples: 335
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- name: test
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num_bytes: 90712
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num_examples: 670
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download_size: 382768
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dataset_size: 685860
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configs:
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- config_name: en
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data_files:
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- split: train
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path: en/train-*
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- split: validation
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path: en/validation-*
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- split: test
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path: en/test-*
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default: true
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---
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# Amazon Multilingual Counterfactual Dataset
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dataset_infos.json
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{"all_languages": {"description": "The dataset contains sentences from Amazon customer reviews (sampled from Amazon product review dataset) annotated for counterfactual detection (CFD) binary classification. Counterfactual statements describe events that did not or cannot take place. Counterfactual statements may be identified as statements of the form \u2013 If p was true, then q would be true (i.e. assertions whose antecedent (p) and consequent (q) are known or assumed to be false).\n", "citation": "@misc{oneill2021i,\n title={I Wish I Would Have Loved This One, But I Didn't -- A Multilingual Dataset for Counterfactual Detection in Product Reviews},\n author={James O'Neill and Polina Rozenshtein and Ryuichi Kiryo and Motoko Kubota and Danushka Bollegala},\n year={2021},\n eprint={2104.06893},\n archivePrefix={arXiv},\n primaryClass={cs.CL}\n}\n", "homepage": "https://github.com/amazon-research/amazon-multilingual-counterfactual-dataset", "license": "CC BY-SA 4.0", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "int32", "id": null, "_type": "Value"}, "label_text": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "amazon_counterfactual", "config_name": "all_languages", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 3304369, "num_examples": 23218, "dataset_name": "amazon_counterfactual"}, "validation": {"name": "validation", "num_bytes": 279231, "num_examples": 1933, "dataset_name": "amazon_counterfactual"}, "test": {"name": "test", "num_bytes": 552017, "num_examples": 3872, "dataset_name": "amazon_counterfactual"}}, "download_checksums": {"data/DE_train.tsv": {"num_bytes": 705786, "checksum": "52710850d8bef30422421f4ca238a4d3e76d44e1e01e2458320b949cd66fbcd1"}, "data/EN_train.tsv": {"num_bytes": 444664, "checksum": "fa1d3db89f133725011f022e1e0bb9ba147b0e9b8b38e15f832ad6192070f7d1"}, "data/EN-ext_train.tsv": {"num_bytes": 857747, "checksum": "eb741daf73fec09af23cb194b6424f533c96280770c7c8a60d87b211a0ae6f72"}, "data/JP_train.tsv": {"num_bytes": 713547, "checksum": "b836056ff3c13c02f56cd5e8d0841e1de45e50f1cc89da10cf42d8c7c5d910a1"}, "data/DE_valid.tsv": {"num_bytes": 60990, "checksum": "677831289a71ebba856dfaecec92dfc9dfade9a954f8e50c923407a1fcda981a"}, "data/EN_valid.tsv": {"num_bytes": 37707, "checksum": "47c981cd724394a45c091998ba9fb553ea5c9159aae228b5009ac32a1e51d6be"}, "data/EN-ext_valid.tsv": {"num_bytes": 71464, "checksum": "3e054c3c83e893cbec0640aeb2d79bf8fabe1040951d127da3f2fa9a69c05002"}, "data/JP_valid.tsv": {"num_bytes": 60656, "checksum": "8ab8efeaa2c271b0b96a74e4c2e3f4cd6b2adc3d588e43c76891f6a259890f11"}, "data/DE_test.tsv": {"num_bytes": 120712, "checksum": "ccfb853849a85ea747fbb435bad7c50336bd2c28c523be4479535a8872870476"}, "data/EN_test.tsv": {"num_bytes": 73457, "checksum": "ca0bbbc8d32e795526b21eba31c6b400e81c192f4d756bafa95c7b71375893d5"}, "data/EN-ext_test.tsv": {"num_bytes": 142278, "checksum": "7891a0dc26417905718389402f6ea57f1a714f81bd258dbd134d5689e2fb7fd6"}, "data/JP_test.tsv": {"num_bytes": 118677, "checksum": "863b45ba88f7e2d3d61f2a7ee1d6b44a11eb13c91653ae563616cc9bee2537a1"}}, "download_size": 3407685, "post_processing_size": null, "dataset_size": 4135617, "size_in_bytes": 7543302}, "de": {"description": "The dataset contains sentences from Amazon customer reviews (sampled from Amazon product review dataset) annotated for counterfactual detection (CFD) binary classification. Counterfactual statements describe events that did not or cannot take place. Counterfactual statements may be identified as statements of the form \u2013 If p was true, then q would be true (i.e. assertions whose antecedent (p) and consequent (q) are known or assumed to be false).\n", "citation": "@misc{oneill2021i,\n title={I Wish I Would Have Loved This One, But I Didn't -- A Multilingual Dataset for Counterfactual Detection in Product Reviews},\n author={James O'Neill and Polina Rozenshtein and Ryuichi Kiryo and Motoko Kubota and Danushka Bollegala},\n year={2021},\n eprint={2104.06893},\n archivePrefix={arXiv},\n primaryClass={cs.CL}\n}\n", "homepage": "https://github.com/amazon-research/amazon-multilingual-counterfactual-dataset", "license": "CC BY-SA 4.0", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "int32", "id": null, "_type": "Value"}, "label_text": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "amazon_counterfactual", "config_name": "de", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 840063, "num_examples": 5600, "dataset_name": "amazon_counterfactual"}, "validation": {"name": "validation", "num_bytes": 72118, "num_examples": 466, "dataset_name": "amazon_counterfactual"}, "test": {"name": "test", "num_bytes": 143102, "num_examples": 934, "dataset_name": "amazon_counterfactual"}}, "download_checksums": {"data/DE_train.tsv": {"num_bytes": 705786, "checksum": "52710850d8bef30422421f4ca238a4d3e76d44e1e01e2458320b949cd66fbcd1"}, "data/DE_valid.tsv": {"num_bytes": 60990, "checksum": "677831289a71ebba856dfaecec92dfc9dfade9a954f8e50c923407a1fcda981a"}, "data/DE_test.tsv": {"num_bytes": 120712, "checksum": "ccfb853849a85ea747fbb435bad7c50336bd2c28c523be4479535a8872870476"}}, "download_size": 887488, "post_processing_size": null, "dataset_size": 1055283, "size_in_bytes": 1942771}, "en": {"description": "The dataset contains sentences from Amazon customer reviews (sampled from Amazon product review dataset) annotated for counterfactual detection (CFD) binary classification. Counterfactual statements describe events that did not or cannot take place. 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