albertvillanova HF staff commited on
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Delete legacy JSON metadata (#2)

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- Delete legacy JSON metadata (22f6020f311be3cecfc298dbd0ac8752c0ee0417)

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  1. dataset_infos.json +0 -1
dataset_infos.json DELETED
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- {"default": {"description": "We study negotiation dialogues where two agents, a buyer and a seller,\nnegotiate over the price of an time for sale. We collected a dataset of more\nthan 6K negotiation dialogues over multiple categories of products scraped from Craigslist.\nOur goal is to develop an agent that negotiates with humans through such conversations.\nThe challenge is to handle both the negotiation strategy and the rich language for bargaining.\n", "citation": "@misc{he2018decoupling,\n title={Decoupling Strategy and Generation in Negotiation Dialogues},\n author={He He and Derek Chen and Anusha Balakrishnan and Percy Liang},\n year={2018},\n eprint={1808.09637},\n archivePrefix={arXiv},\n primaryClass={cs.CL}\n}\n", "homepage": "https://stanfordnlp.github.io/cocoa/", "license": "", "features": {"agent_info": {"feature": {"Bottomline": {"dtype": "string", "id": null, "_type": "Value"}, "Role": {"dtype": "string", "id": null, "_type": "Value"}, "Target": {"dtype": "float32", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "agent_turn": {"feature": {"dtype": "int32", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "dialogue_acts": {"feature": {"intent": {"dtype": "string", "id": null, "_type": "Value"}, "price": {"dtype": "float32", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "utterance": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "items": {"feature": {"Category": {"dtype": "string", "id": null, "_type": "Value"}, "Images": {"dtype": "string", "id": null, "_type": "Value"}, "Price": {"dtype": "float32", "id": null, "_type": "Value"}, "Description": {"dtype": "string", "id": null, "_type": "Value"}, "Title": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "craigslist_bargains", "config_name": "default", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 8538836, "num_examples": 5247, "dataset_name": "craigslist_bargains"}, "test": {"name": "test", "num_bytes": 1353933, "num_examples": 838, "dataset_name": "craigslist_bargains"}, "validation": {"name": "validation", "num_bytes": 966032, "num_examples": 597, "dataset_name": "craigslist_bargains"}}, "download_checksums": {"https://worksheets.codalab.org/rest/bundles/0xd34bbbc5fb3b4fccbd19e10756ca8dd7/contents/blob/parsed.json": {"num_bytes": 20148723, "checksum": "34033ff87565b9fc9eb0efe867e9d3e32456dbe1528cd1683f94a84b09f66ace"}, "https://worksheets.codalab.org/rest/bundles/0x15c4160b43d44ee3a8386cca98da138c/contents/blob/parsed.json": {"num_bytes": 2287054, "checksum": "03b35dc18bd90d87dac46893ac4db8ab3eed51786d192975be68d3bab38e306e"}, "https://worksheets.codalab.org/rest/bundles/0x54d325bbcfb2463583995725ed8ca42b/contents/blob/": {"num_bytes": 2937841, "checksum": "c802f15f80ea3066d429375393319d7234daacbd6a26a6ad5afd0ad78a2f7736"}}, "download_size": 25373618, "post_processing_size": null, "dataset_size": 10858801, "size_in_bytes": 36232419}}