dataset_infos.json

{"light": {"description": "AmbigNQ, a dataset covering 14,042 questions from NQ-open, an existing open-domain QA benchmark. We find that over half of the questions in NQ-open are ambiguous. The types of ambiguity are diverse and sometimes subtle, many of which are only apparent after examining evidence provided by a very large text corpus.  AMBIGNQ, a dataset with\n14,042 annotations on NQ-OPEN questions containing diverse types of ambiguity.\nWe provide two distributions of our new dataset AmbigNQ: a full version with all annotation metadata and a light version with only inputs and outputs.\n", "citation": "@inproceedings{ min2020ambigqa,\n    title={ {A}mbig{QA}: Answering Ambiguous Open-domain Questions },\n    author={ Min, Sewon and Michael, Julian and Hajishirzi, Hannaneh and Zettlemoyer, Luke },\n    booktitle={ EMNLP },\n    year={2020}\n}\n", "homepage": "https://nlp.cs.washington.edu/ambigqa/", "license": "CC BY-SA 3.0", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "annotations": {"feature": {"type": {"dtype": "string", "id": null, "_type": "Value"}, "answer": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "qaPairs": {"feature": {"question": {"dtype": "string", "id": null, "_type": "Value"}, "answer": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "ambig_qa", "config_name": "light", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2739732, "num_examples": 10036, "dataset_name": "ambig_qa"}, "validation": {"name": "validation", "num_bytes": 805808, "num_examples": 2002, "dataset_name": "ambig_qa"}}, "download_checksums": {"https://nlp.cs.washington.edu/ambigqa/data/ambignq_light.zip": {"num_bytes": 1061383, "checksum": "3f5dada69dec05cef1533a64945cd7bafde1aa94b0cdd6fa9a22f881206220db"}, "https://nlp.cs.washington.edu/ambigqa/data/ambignq.zip": {"num_bytes": 18639517, "checksum": "e85cec5909f076c6f584322c7f05cae44dcacaec93758c110a26fcceaa8da0ce"}}, "download_size": 19700900, "post_processing_size": null, "dataset_size": 3545540, "size_in_bytes": 23246440}, "full": {"description": "AmbigNQ, a dataset covering 14,042 questions from NQ-open, an existing open-domain QA benchmark. We find that over half of the questions in NQ-open are ambiguous. The types of ambiguity are diverse and sometimes subtle, many of which are only apparent after examining evidence provided by a very large text corpus.  AMBIGNQ, a dataset with\n14,042 annotations on NQ-OPEN questions containing diverse types of ambiguity.\nWe provide two distributions of our new dataset AmbigNQ: a full version with all annotation metadata and a light version with only inputs and outputs.\n", "citation": "@inproceedings{ min2020ambigqa,\n    title={ {A}mbig{QA}: Answering Ambiguous Open-domain Questions },\n    author={ Min, Sewon and Michael, Julian and Hajishirzi, Hannaneh and Zettlemoyer, Luke },\n    booktitle={ EMNLP },\n    year={2020}\n}\n", "homepage": "https://nlp.cs.washington.edu/ambigqa/", "license": "CC BY-SA 3.0", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "annotations": {"feature": {"type": {"dtype": "string", "id": null, "_type": "Value"}, "answer": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "qaPairs": {"feature": {"question": {"dtype": "string", "id": null, "_type": "Value"}, "answer": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "viewed_doc_titles": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "used_queries": {"feature": {"query": {"dtype": "string", "id": null, "_type": "Value"}, "results": {"feature": {"title": {"dtype": "string", "id": null, "_type": "Value"}, "snippet": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "nq_answer": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "nq_doc_title": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "ambig_qa", "config_name": "full", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 43538733, "num_examples": 10036, "dataset_name": "ambig_qa"}, "validation": {"name": "validation", "num_bytes": 15383368, "num_examples": 2002, "dataset_name": "ambig_qa"}}, "download_checksums": {"https://nlp.cs.washington.edu/ambigqa/data/ambignq_light.zip": {"num_bytes": 1061383, "checksum": "3f5dada69dec05cef1533a64945cd7bafde1aa94b0cdd6fa9a22f881206220db"}, "https://nlp.cs.washington.edu/ambigqa/data/ambignq.zip": {"num_bytes": 18639517, "checksum": "e85cec5909f076c6f584322c7f05cae44dcacaec93758c110a26fcceaa8da0ce"}}, "download_size": 19700900, "post_processing_size": null, "dataset_size": 58922101, "size_in_bytes": 78623001}}