| {"default": {"description": "Recent work in semantic parsing for question answering has focused on long and complicated questions, many of which would seem unnatural if asked in a normal conversation between two humans. In an effort to explore a conversational QA setting, we present a more realistic task: answering sequences of simple but inter-related questions. We created SQA by asking crowdsourced workers to decompose 2,022 questions from WikiTableQuestions (WTQ), which contains highly-compositional questions about tables from Wikipedia. We had three workers decompose each WTQ question, resulting in a dataset of 6,066 sequences that contain 17,553 questions in total. Each question is also associated with answers in the form of cell locations in the tables.\n", "citation": "@inproceedings{iyyer2017search,\n title={Search-based neural structured learning for sequential question answering},\n author={Iyyer, Mohit and Yih, Wen-tau and Chang, Ming-Wei},\n booktitle={Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},\n pages={1821--1831},\n year={2017}\n}\n", "homepage": "https://msropendata.com/datasets/b25190ed-0f59-47b1-9211-5962858142c2", "license": "Microsoft Research Data License Agreement", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "annotator": {"dtype": "int32", "id": null, "_type": "Value"}, "position": {"dtype": "int32", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "table_file": {"dtype": "string", "id": null, "_type": "Value"}, "table_header": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "table_data": {"feature": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "length": -1, "id": null, "_type": "Sequence"}, "answer_coordinates": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "answer_text": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "msr_sqa", "config_name": "default", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 22605449, "num_examples": 14541, "dataset_name": "msr_sqa"}, "test": {"name": "test", "num_bytes": 4924516, "num_examples": 3012, "dataset_name": "msr_sqa"}}, "download_checksums": {"https://download.microsoft.com/download/1/D/C/1DC270D2-1B53-4A61-A2E3-88AB3E4E6E1F/SQA%20Release%201.0.zip": {"num_bytes": 4796932, "checksum": "791a07ef90d6e736c186b25009d3c10cb38624b879bb668033445a3ab8892f64"}}, "download_size": 4796932, "post_processing_size": null, "dataset_size": 27529965, "size_in_bytes": 32326897}} |