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README.md

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----
-annotations_creators:
-- crowdsourced
-language:
-- en
-language_creators:
-- found
-license:
-- other
-multilinguality:
-- monolingual
-pretty_name: 'CoQA: Conversational Question Answering Challenge'
-size_categories:
-- 1K<n<10K
-source_datasets:
-- extended|race
-- extended|cnn_dailymail
-- extended|wikipedia
-- extended|other
-task_categories:
-- question-answering
-task_ids:
-- extractive-qa
-paperswithcode_id: coqa
-tags:
-- conversational-qa
-dataset_info:
-  features:
-  - name: source
-    dtype: string
-  - name: story
-    dtype: string
-  - name: questions
-    sequence: string
-  - name: answers
-    sequence:
-    - name: input_text
-      dtype: string
-    - name: answer_start
-      dtype: int32
-    - name: answer_end
-      dtype: int32
-  splits:
-  - name: train
-    num_bytes: 17981459
-    num_examples: 7199
-  - name: validation
-    num_bytes: 1225518
-    num_examples: 500
-  download_size: 58092681
-  dataset_size: 19206977
----
-
-# Dataset Card for "coqa"
-
-## 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://stanfordnlp.github.io/coqa/](https://stanfordnlp.github.io/coqa/)
-- **Repository:** https://github.com/stanfordnlp/coqa-baselines
-- **Paper:** [CoQA: A Conversational Question Answering Challenge](https://arxiv.org/abs/1808.07042)
-- **Point of Contact:** [Google Group](https://groups.google.com/forum/#!forum/coqa), [Siva Reddy](mailto:[email protected]), [Danqi Chen](mailto:[email protected])
-- **Size of downloaded dataset files:** 55.40 MB
-- **Size of the generated dataset:** 18.35 MB
-- **Total amount of disk used:** 73.75 MB
-
-### Dataset Summary
-
-CoQA is a large-scale dataset for building Conversational Question Answering systems.
-
-Our dataset contains 127k questions with answers, obtained from 8k conversations about text passages from seven diverse domains. The questions are conversational, and the answers are free-form text with their corresponding evidence highlighted in the passage.
-
-### 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:** 55.40 MB
-- **Size of the generated dataset:** 18.35 MB
-- **Total amount of disk used:** 73.75 MB
-
-An example of 'train' looks as follows.
-```
-This example was too long and was cropped:
-
-{
-    "answers": "{\"answer_end\": [179, 494, 511, 545, 879, 1127, 1128, 94, 150, 412, 1009, 1046, 643, -1, 764, 724, 125, 1384, 881, 910], \"answer_...",
-    "questions": "[\"When was the Vat formally opened?\", \"what is the library for?\", \"for what subjects?\", \"and?\", \"what was started in 2014?\", \"ho...",
-    "source": "wikipedia",
-    "story": "\"The Vatican Apostolic Library (), more commonly called the Vatican Library or simply the Vat, is the library of the Holy See, l..."
-}
-```
-
-### Data Fields
-
-The data fields are the same among all splits.
-
-#### default
-- `source`: a `string` feature.
-- `story`: a `string` feature.
-- `questions`: a `list` of `string` features.
-- `answers`: a dictionary feature containing:
-  - `input_text`: a `string` feature.
-  - `answer_start`: a `int32` feature.
-  - `answer_end`: a `int32` feature.
-
-### Data Splits
-
-| name  |train|validation|
-|-------|----:|---------:|
-|default| 7199|       500|
-
-## 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
-
-CoQA contains passages from seven domains. We make five of these public under the following licenses:
-- Literature and Wikipedia passages are shared under [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/) license.
-- Children's stories are collected from [MCTest](https://www.microsoft.com/en-us/research/publication/mctest-challenge-dataset-open-domain-machine-comprehension-text/) which comes with [MSR-LA](https://github.com/mcobzarenco/mctest/blob/master/data/MCTest/LICENSE.pdf) license.
-- Middle/High school exam passages are collected from [RACE](https://arxiv.org/abs/1704.04683) which comes with its [own](http://www.cs.cmu.edu/~glai1/data/race/) license.
-- News passages are collected from the [DeepMind CNN dataset](https://arxiv.org/abs/1506.03340) which comes with [Apache](https://github.com/deepmind/rc-data/blob/master/LICENSE) license. 
-
-### Citation Information
-
-```
-@article{reddy-etal-2019-coqa,
-    title = "{C}o{QA}: A Conversational Question Answering Challenge",
-    author = "Reddy, Siva  and
-      Chen, Danqi  and
-      Manning, Christopher D.",
-    journal = "Transactions of the Association for Computational Linguistics",
-    volume = "7",
-    year = "2019",
-    address = "Cambridge, MA",
-    publisher = "MIT Press",
-    url = "https://aclanthology.org/Q19-1016",
-    doi = "10.1162/tacl_a_00266",
-    pages = "249--266",
-}
-```
-
-### Contributions
-
-Thanks to [@patrickvonplaten](https://github.com/patrickvonplaten), [@lewtun](https://github.com/lewtun), [@thomwolf](https://github.com/thomwolf), [@mariamabarham](https://github.com/mariamabarham), [@ojasaar](https://github.com/ojasaar), [@lhoestq](https://github.com/lhoestq) for adding this dataset.

coqa.py

@@ -1,91 +0,0 @@
-"""CoQA dataset."""
-
-
-import json
-
-import datasets
-
-
-_HOMEPAGE = "https://stanfordnlp.github.io/coqa/"
-
-_CITATION = """\
-@article{reddy-etal-2019-coqa,
-    title = "{C}o{QA}: A Conversational Question Answering Challenge",
-    author = "Reddy, Siva  and
-      Chen, Danqi  and
-      Manning, Christopher D.",
-    journal = "Transactions of the Association for Computational Linguistics",
-    volume = "7",
-    year = "2019",
-    address = "Cambridge, MA",
-    publisher = "MIT Press",
-    url = "https://aclanthology.org/Q19-1016",
-    doi = "10.1162/tacl_a_00266",
-    pages = "249--266",
-}
-"""
-
-_DESCRIPTION = """\
-CoQA: A Conversational Question Answering Challenge
-"""
-
-_TRAIN_DATA_URL = "https://nlp.stanford.edu/data/coqa/coqa-train-v1.0.json"
-_DEV_DATA_URL = "https://nlp.stanford.edu/data/coqa/coqa-dev-v1.0.json"
-
-
-class Coqa(datasets.GeneratorBasedBuilder):
-
-    VERSION = datasets.Version("1.0.0")
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "source": datasets.Value("string"),
-                    "story": datasets.Value("string"),
-                    "questions": datasets.features.Sequence(datasets.Value("string")),
-                    "answers": datasets.features.Sequence(
-                        {
-                            "input_text": datasets.Value("string"),
-                            "answer_start": datasets.Value("int32"),
-                            "answer_end": datasets.Value("int32"),
-                        }
-                    ),
-                }
-            ),
-            homepage=_HOMEPAGE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        urls_to_download = {"train": _TRAIN_DATA_URL, "dev": _DEV_DATA_URL}
-        downloaded_files = dl_manager.download_and_extract(urls_to_download)
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"], "split": "train"}
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"], "split": "validation"}
-            ),
-        ]
-
-    def _generate_examples(self, filepath, split):
-        """Yields examples."""
-        with open(filepath, encoding="utf-8") as f:
-            data = json.load(f)
-            for row in data["data"]:
-                questions = [question["input_text"] for question in row["questions"]]
-                story = row["story"]
-                source = row["source"]
-                answers_start = [answer["span_start"] for answer in row["answers"]]
-                answers_end = [answer["span_end"] for answer in row["answers"]]
-                answers = [answer["input_text"] for answer in row["answers"]]
-                yield row["id"], {
-                    "source": source,
-                    "story": story,
-                    "questions": questions,
-                    "answers": {"input_text": answers, "answer_start": answers_start, "answer_end": answers_end},
-                }

dataset_infos.json

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-{"default": {"description": "CoQA: A Conversational Question Answering Challenge\n", "citation": "@article{reddy-etal-2019-coqa,\n    title = \"{C}o{QA}: A Conversational Question Answering Challenge\",\n    author = \"Reddy, Siva  and\n      Chen, Danqi  and\n      Manning, Christopher D.\",\n    journal = \"Transactions of the Association for Computational Linguistics\",\n    volume = \"7\",\n    year = \"2019\",\n    address = \"Cambridge, MA\",\n    publisher = \"MIT Press\",\n    url = \"https://aclanthology.org/Q19-1016\",\n    doi = \"10.1162/tacl_a_00266\",\n    pages = \"249--266\",\n}\n", "homepage": "https://stanfordnlp.github.io/coqa/", "license": "", "features": {"source": {"dtype": "string", "id": null, "_type": "Value"}, "story": {"dtype": "string", "id": null, "_type": "Value"}, "questions": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "answers": {"feature": {"input_text": {"dtype": "string", "id": null, "_type": "Value"}, "answer_start": {"dtype": "int32", "id": null, "_type": "Value"}, "answer_end": {"dtype": "int32", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "coqa", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 17981459, "num_examples": 7199, "dataset_name": "coqa"}, "validation": {"name": "validation", "num_bytes": 1225518, "num_examples": 500, "dataset_name": "coqa"}}, "download_checksums": {"https://nlp.stanford.edu/data/coqa/coqa-train-v1.0.json": {"num_bytes": 49001836, "checksum": "b0fdb2bc1bd38dd3ca2ce5fa2ac3e02c6288ac914f241ac409a655ffb6619fa6"}, "https://nlp.stanford.edu/data/coqa/coqa-dev-v1.0.json": {"num_bytes": 9090845, "checksum": "dfa367a9733ce53222918d0231d9b3bedc2b8ee831a2845f62dfc70701f2540a"}}, "download_size": 58092681, "post_processing_size": null, "dataset_size": 19206977, "size_in_bytes": 77299658}}

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