Datasets:
head_qa

- {"es": {"description": "HEAD-QA is a multi-choice HEAlthcare Dataset. The questions come from exams to access a specialized position in the\nSpanish healthcare system, and are challenging even for highly specialized humans. They are designed by the Ministerio\nde Sanidad, Consumo y Bienestar Social.\n\nThe dataset contains questions about the following topics: medicine, nursing, psychology, chemistry, pharmacology and biology.\n", "citation": "@inproceedings{vilares-gomez-rodriguez-2019-head,\n title = \"{HEAD}-{QA}: A Healthcare Dataset for Complex Reasoning\",\n author = \"Vilares, David and\n G{'o}mez-Rodr{'i}guez, Carlos\",\n booktitle = \"Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics\",\n month = jul,\n year = \"2019\",\n address = \"Florence, Italy\",\n publisher = \"Association for Computational Linguistics\",\n url = \"https://www.aclweb.org/anthology/P19-1092\",\n doi = \"10.18653/v1/P19-1092\",\n pages = \"960--966\",\n abstract = \"We present HEAD-QA, a multi-choice question answering testbed to encourage research on complex reasoning. The questions come from exams to access a specialized position in the Spanish healthcare system, and are challenging even for highly specialized humans. We then consider monolingual (Spanish) and cross-lingual (to English) experiments with information retrieval and neural techniques. We show that: (i) HEAD-QA challenges current methods, and (ii) the results lag well behind human performance, demonstrating its usefulness as a benchmark for future work.\",\n}\n", "homepage": "https://aghie.github.io/head-qa/", "license": "MIT License", "features": {"name": {"dtype": "string", "id": null, "_type": "Value"}, "year": {"dtype": "string", "id": null, "_type": "Value"}, "category": {"dtype": "string", "id": null, "_type": "Value"}, "qid": {"dtype": "int32", "id": null, "_type": "Value"}, "qtext": {"dtype": "string", "id": null, "_type": "Value"}, "ra": {"dtype": "int32", "id": null, "_type": "Value"}, "image": {"decode": true, "id": null, "_type": "Image"}, "answers": [{"aid": {"dtype": "int32", "id": null, "_type": "Value"}, "atext": {"dtype": "string", "id": null, "_type": "Value"}}]}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "head_qa", "config_name": "es", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1229678, "num_examples": 2657, "dataset_name": "head_qa"}, "test": {"name": "test", "num_bytes": 1204006, "num_examples": 2742, "dataset_name": "head_qa"}, "validation": {"name": "validation", "num_bytes": 573354, "num_examples": 1366, "dataset_name": "head_qa"}}, "download_checksums": {"https://huggingface.co/datasets/head_qa/resolve/main/data/head-qa-es-en-pdfs.zip": {"num_bytes": 79365502, "checksum": "6ec29a3f55153d167f0bdf05395558919ba0b1df9c63e79ffceda2a09884ad8b"}}, "download_size": 79365502, "post_processing_size": null, "dataset_size": 3007038, "size_in_bytes": 82372540}, "en": {"description": "HEAD-QA is a multi-choice HEAlthcare Dataset. The questions come from exams to access a specialized position in the\nSpanish healthcare system, and are challenging even for highly specialized humans. They are designed by the Ministerio\nde Sanidad, Consumo y Bienestar Social.\n\nThe dataset contains questions about the following topics: medicine, nursing, psychology, chemistry, pharmacology and biology.\n", "citation": "@inproceedings{vilares-gomez-rodriguez-2019-head,\n title = \"{HEAD}-{QA}: A Healthcare Dataset for Complex Reasoning\",\n author = \"Vilares, David and\n G{'o}mez-Rodr{'i}guez, Carlos\",\n booktitle = \"Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics\",\n month = jul,\n year = \"2019\",\n address = \"Florence, Italy\",\n publisher = \"Association for Computational Linguistics\",\n url = \"https://www.aclweb.org/anthology/P19-1092\",\n doi = \"10.18653/v1/P19-1092\",\n pages = \"960--966\",\n abstract = \"We present HEAD-QA, a multi-choice question answering testbed to encourage research on complex reasoning. The questions come from exams to access a specialized position in the Spanish healthcare system, and are challenging even for highly specialized humans. We then consider monolingual (Spanish) and cross-lingual (to English) experiments with information retrieval and neural techniques. We show that: (i) HEAD-QA challenges current methods, and (ii) the results lag well behind human performance, demonstrating its usefulness as a benchmark for future work.\",\n}\n", "homepage": "https://aghie.github.io/head-qa/", "license": "MIT License", "features": {"name": {"dtype": "string", "id": null, "_type": "Value"}, "year": {"dtype": "string", "id": null, "_type": "Value"}, "category": {"dtype": "string", "id": null, "_type": "Value"}, "qid": {"dtype": "int32", "id": null, "_type": "Value"}, "qtext": {"dtype": "string", "id": null, "_type": "Value"}, "ra": {"dtype": "int32", "id": null, "_type": "Value"}, "image": {"decode": true, "id": null, "_type": "Image"}, "answers": [{"aid": {"dtype": "int32", "id": null, "_type": "Value"}, "atext": {"dtype": "string", "id": null, "_type": "Value"}}]}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "head_qa", "config_name": "en", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1156808, "num_examples": 2657, "dataset_name": "head_qa"}, "test": {"name": "test", "num_bytes": 1131536, "num_examples": 2742, "dataset_name": "head_qa"}, "validation": {"name": "validation", "num_bytes": 539892, "num_examples": 1366, "dataset_name": "head_qa"}}, "download_checksums": {"https://huggingface.co/datasets/head_qa/resolve/main/data/head-qa-es-en-pdfs.zip": {"num_bytes": 79365502, "checksum": "6ec29a3f55153d167f0bdf05395558919ba0b1df9c63e79ffceda2a09884ad8b"}}, "download_size": 79365502, "post_processing_size": null, "dataset_size": 2828236, "size_in_bytes": 82193738}}