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README.md

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----
-annotations_creators:
-- crowdsourced
-language_creators:
-- crowdsourced
-language:
-- zh
-license:
-- cc-by-sa-4.0
-multilinguality:
-- monolingual
-size_categories:
-- 10K<n<100K
-source_datasets:
-- original
-task_categories:
-- question-answering
-task_ids:
-- extractive-qa
-paperswithcode_id: cmrc-2018
-pretty_name: Chinese Machine Reading Comprehension 2018
-dataset_info:
-  features:
-  - name: id
-    dtype: string
-  - name: context
-    dtype: string
-  - name: question
-    dtype: string
-  - name: answers
-    sequence:
-    - name: text
-      dtype: string
-    - name: answer_start
-      dtype: int32
-  splits:
-  - name: train
-    num_bytes: 15508110
-    num_examples: 10142
-  - name: validation
-    num_bytes: 5183809
-    num_examples: 3219
-  - name: test
-    num_bytes: 1606931
-    num_examples: 1002
-  download_size: 11508117
-  dataset_size: 22298850
----
-
-# Dataset Card for "cmrc2018"
-
-## Table of Contents
-- [Dataset Description](#dataset-description)
-  - [Dataset Summary](#dataset-summary)
-  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
-  - [Languages](#languages)
-- [Dataset Structure](#dataset-structure)
-  - [Data Instances](#data-instances)
-  - [Data Fields](#data-fields)
-  - [Data Splits](#data-splits)
-- [Dataset Creation](#dataset-creation)
-  - [Curation Rationale](#curation-rationale)
-  - [Source Data](#source-data)
-  - [Annotations](#annotations)
-  - [Personal and Sensitive Information](#personal-and-sensitive-information)
-- [Considerations for Using the Data](#considerations-for-using-the-data)
-  - [Social Impact of Dataset](#social-impact-of-dataset)
-  - [Discussion of Biases](#discussion-of-biases)
-  - [Other Known Limitations](#other-known-limitations)
-- [Additional Information](#additional-information)
-  - [Dataset Curators](#dataset-curators)
-  - [Licensing Information](#licensing-information)
-  - [Citation Information](#citation-information)
-  - [Contributions](#contributions)
-
-## Dataset Description
-
-- **Homepage:** [https://github.com/ymcui/cmrc2018](https://github.com/ymcui/cmrc2018)
-- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-- **Size of downloaded dataset files:** 10.97 MB
-- **Size of the generated dataset:** 21.28 MB
-- **Total amount of disk used:** 32.26 MB
-
-### Dataset Summary
-
-A Span-Extraction dataset for Chinese machine reading comprehension to add language
-diversities in this area. The dataset is composed by near 20,000 real questions annotated
-on Wikipedia paragraphs by human experts. We also annotated a challenge set which
-contains the questions that need comprehensive understanding and multi-sentence
-inference throughout the context.
-
-### Supported Tasks and Leaderboards
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Languages
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-## Dataset Structure
-
-### Data Instances
-
-#### default
-
-- **Size of downloaded dataset files:** 10.97 MB
-- **Size of the generated dataset:** 21.28 MB
-- **Total amount of disk used:** 32.26 MB
-
-An example of 'validation' looks as follows.
-```
-This example was too long and was cropped:
-
-{
-    "answers": {
-        "answer_start": [11, 11],
-        "text": ["光荣和ω-force", "光荣和ω-force"]
-    },
-    "context": "\"《战国无双3》（）是由光荣和ω-force开发的战国无双系列的正统第三续作。本作以三大故事为主轴，分别是以武田信玄等人为主的《关东三国志》，织田信长等人为主的《战国三杰》，石田三成等人为主的《关原的年轻武者》，丰富游戏内的剧情。此部份专门介绍角色，欲知武...",
-    "id": "DEV_0_QUERY_0",
-    "question": "《战国无双3》是由哪两个公司合作开发的？"
-}
-```
-
-### Data Fields
-
-The data fields are the same among all splits.
-
-#### default
-- `id`: a `string` feature.
-- `context`: a `string` feature.
-- `question`: a `string` feature.
-- `answers`: a dictionary feature containing:
-  - `text`: a `string` feature.
-  - `answer_start`: a `int32` feature.
-
-### Data Splits
-
-| name    | train | validation | test |
-| ------- | ----: | ---------: | ---: |
-| default | 10142 |       3219 | 1002 |
-
-## Dataset Creation
-
-### Curation Rationale
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Source Data
-
-#### Initial Data Collection and Normalization
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-#### Who are the source language producers?
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Annotations
-
-#### Annotation process
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-#### Who are the annotators?
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Personal and Sensitive Information
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-## Considerations for Using the Data
-
-### Social Impact of Dataset
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Discussion of Biases
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Other Known Limitations
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-## Additional Information
-
-### Dataset Curators
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Licensing Information
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Citation Information
-
-```
-@inproceedings{cui-emnlp2019-cmrc2018,
-    title = "A Span-Extraction Dataset for {C}hinese Machine Reading Comprehension",
-    author = "Cui, Yiming  and
-      Liu, Ting  and
-      Che, Wanxiang  and
-      Xiao, Li  and
-      Chen, Zhipeng  and
-      Ma, Wentao  and
-      Wang, Shijin  and
-      Hu, Guoping",
-    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)",
-    month = nov,
-    year = "2019",
-    address = "Hong Kong, China",
-    publisher = "Association for Computational Linguistics",
-    url = "https://www.aclweb.org/anthology/D19-1600",
-    doi = "10.18653/v1/D19-1600",
-    pages = "5886--5891",
-}
-
-```
-
-
-### Contributions
-
-Thanks to [@patrickvonplaten](https://github.com/patrickvonplaten), [@mariamabarham](https://github.com/mariamabarham), [@lewtun](https://github.com/lewtun), [@thomwolf](https://github.com/thomwolf) for adding this dataset.

cmrc2018.py

@@ -1,123 +0,0 @@
-"""TODO(cmrc2018): Add a description here."""
-
-
-import json
-
-import datasets
-from datasets.tasks import QuestionAnsweringExtractive
-
-
-# TODO(cmrc2018): BibTeX citation
-_CITATION = """\
-@inproceedings{cui-emnlp2019-cmrc2018,
-    title = {A Span-Extraction Dataset for {C}hinese Machine Reading Comprehension},
-    author = {Cui, Yiming  and
-      Liu, Ting  and
-      Che, Wanxiang  and
-      Xiao, Li  and
-      Chen, Zhipeng  and
-      Ma, Wentao  and
-      Wang, Shijin  and
-      Hu, Guoping},
-    booktitle = {Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)},
-    month = {nov},
-    year = {2019},
-    address = {Hong Kong, China},
-    publisher = {Association for Computational Linguistics},
-    url = {https://www.aclweb.org/anthology/D19-1600},
-    doi = {10.18653/v1/D19-1600},
-    pages = {5886--5891}}
-"""
-
-# TODO(cmrc2018):
-_DESCRIPTION = """\
-A Span-Extraction dataset for Chinese machine reading comprehension to add language
-diversities in this area. The dataset is composed by near 20,000 real questions annotated
-on Wikipedia paragraphs by human experts. We also annotated a challenge set which
-contains the questions that need comprehensive understanding and multi-sentence
-inference throughout the context.
-"""
-_URL = "https://github.com/ymcui/cmrc2018"
-_TRAIN_FILE = "https://worksheets.codalab.org/rest/bundles/0x15022f0c4d3944a599ab27256686b9ac/contents/blob/"
-_DEV_FILE = "https://worksheets.codalab.org/rest/bundles/0x72252619f67b4346a85e122049c3eabd/contents/blob/"
-_TEST_FILE = "https://worksheets.codalab.org/rest/bundles/0x182c2e71fac94fc2a45cc1a3376879f7/contents/blob/"
-
-
-class Cmrc2018(datasets.GeneratorBasedBuilder):
-    """TODO(cmrc2018): Short description of my dataset."""
-
-    # TODO(cmrc2018): Set up version.
-    VERSION = datasets.Version("0.1.0")
-
-    def _info(self):
-        # TODO(cmrc2018): Specifies the datasets.DatasetInfo object
-        return datasets.DatasetInfo(
-            # This is the description that will appear on the datasets page.
-            description=_DESCRIPTION,
-            # datasets.features.FeatureConnectors
-            features=datasets.Features(
-                {
-                    "id": datasets.Value("string"),
-                    "context": datasets.Value("string"),
-                    "question": datasets.Value("string"),
-                    "answers": datasets.features.Sequence(
-                        {
-                            "text": datasets.Value("string"),
-                            "answer_start": datasets.Value("int32"),
-                        }
-                    ),
-                    # These are the features of your dataset like images, labels ...
-                }
-            ),
-            # If there's a common (input, target) tuple from the features,
-            # specify them here. They'll be used if as_supervised=True in
-            # builder.as_dataset.
-            supervised_keys=None,
-            # Homepage of the dataset for documentation
-            homepage=_URL,
-            citation=_CITATION,
-            task_templates=[
-                QuestionAnsweringExtractive(
-                    question_column="question", context_column="context", answers_column="answers"
-                )
-            ],
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        # TODO(cmrc2018): Downloads the data and defines the splits
-        # dl_manager is a datasets.download.DownloadManager that can be used to
-        # download and extract URLs
-        urls_to_download = {"train": _TRAIN_FILE, "dev": _DEV_FILE, "test": _TEST_FILE}
-        downloaded_files = dl_manager.download_and_extract(urls_to_download)
-
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
-            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
-        ]
-
-    def _generate_examples(self, filepath):
-        """Yields examples."""
-        # TODO(cmrc2018): Yields (key, example) tuples from the dataset
-        with open(filepath, encoding="utf-8") as f:
-            data = json.load(f)
-            for example in data["data"]:
-                for paragraph in example["paragraphs"]:
-                    context = paragraph["context"].strip()
-                    for qa in paragraph["qas"]:
-                        question = qa["question"].strip()
-                        id_ = qa["id"]
-
-                        answer_starts = [answer["answer_start"] for answer in qa["answers"]]
-                        answers = [answer["text"].strip() for answer in qa["answers"]]
-
-                        yield id_, {
-                            "context": context,
-                            "question": question,
-                            "id": id_,
-                            "answers": {
-                                "answer_start": answer_starts,
-                                "text": answers,
-                            },
-                        }

dataset_infos.json

@@ -1 +0,0 @@
-{"default": {"description": "A Span-Extraction dataset for Chinese machine reading comprehension to add language\ndiversities in this area. The dataset is composed by near 20,000 real questions annotated\non Wikipedia paragraphs by human experts. We also annotated a challenge set which\ncontains the questions that need comprehensive understanding and multi-sentence\ninference throughout the context.\n", "citation": "@inproceedings{cui-emnlp2019-cmrc2018,\n    title = {A Span-Extraction Dataset for {C}hinese Machine Reading Comprehension},\n    author = {Cui, Yiming  and\n      Liu, Ting  and\n      Che, Wanxiang  and\n      Xiao, Li  and\n      Chen, Zhipeng  and\n      Ma, Wentao  and\n      Wang, Shijin  and\n      Hu, Guoping},\n    booktitle = {Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)},\n    month = {nov},\n    year = {2019},\n    address = {Hong Kong, China},\n    publisher = {Association for Computational Linguistics},\n    url = {https://www.aclweb.org/anthology/D19-1600},\n    doi = {10.18653/v1/D19-1600},\n    pages = {5886--5891}}\n", "homepage": "https://github.com/ymcui/cmrc2018", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "context": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "answers": {"feature": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "answer_start": {"dtype": "int32", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": [{"task": "question-answering-extractive", "question_column": "question", "context_column": "context", "answers_column": "answers"}], "builder_name": "cmrc2018", "config_name": "default", "version": {"version_str": "0.1.0", "description": null, "major": 0, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 15508110, "num_examples": 10142, "dataset_name": "cmrc2018"}, "validation": {"name": "validation", "num_bytes": 5183809, "num_examples": 3219, "dataset_name": "cmrc2018"}, "test": {"name": "test", "num_bytes": 1606931, "num_examples": 1002, "dataset_name": "cmrc2018"}}, "download_checksums": {"https://worksheets.codalab.org/rest/bundles/0x15022f0c4d3944a599ab27256686b9ac/contents/blob/": {"num_bytes": 7408757, "checksum": "5497aa2f81908e31d6b0e27d99b1f90ab63a8f58fa92fffe5d17cf62eba0c212"}, "https://worksheets.codalab.org/rest/bundles/0x72252619f67b4346a85e122049c3eabd/contents/blob/": {"num_bytes": 3299139, "checksum": "e9ff74231f05c230c6fa88b84441ee334d97234cbb610991cd94b82db00c7f1f"}, "https://worksheets.codalab.org/rest/bundles/0x182c2e71fac94fc2a45cc1a3376879f7/contents/blob/": {"num_bytes": 800221, "checksum": "f3fae95b57da8e03afb2b57467dd221417060ef4d82db13bf22fc88589f3a6f3"}}, "download_size": 11508117, "post_processing_size": null, "dataset_size": 22298850, "size_in_bytes": 33806967}}

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