Convert dataset to Parquet

Convert dataset to Parquet.

README.md

@@ -1,15 +1,14 @@
 ---
 annotations_creators:
 - crowdsourced
-language:
-- en
 language_creators:
 - found
+language:
+- en
 license:
 - cc-by-nc-sa-4.0
 multilinguality:
 - monolingual
-pretty_name: Question Answering for Artificial Intelligence (QuAIL)
 size_categories:
 - 10K<n<100K
 source_datasets:
@@ -19,7 +18,9 @@ task_categories:
 task_ids:
 - multiple-choice-qa
 paperswithcode_id: quail
+pretty_name: Question Answering for Artificial Intelligence (QuAIL)
 dataset_info:
+  config_name: quail
   features:
   - name: id
     dtype: string
@@ -47,19 +48,28 @@ dataset_info:
     sequence: string
   - name: correct_answer_id
     dtype: int32
-  config_name: quail
   splits:
   - name: train
-    num_bytes: 23432697
+    num_bytes: 23432601
     num_examples: 10246
   - name: validation
-    num_bytes: 4989579
+    num_bytes: 4989531
     num_examples: 2164
   - name: challenge
-    num_bytes: 1199840
+    num_bytes: 1199792
     num_examples: 556
-  download_size: 6402933
-  dataset_size: 29622116
+  download_size: 2286403
+  dataset_size: 29621924
+configs:
+- config_name: quail
+  data_files:
+  - split: train
+    path: quail/train-*
+  - split: validation
+    path: quail/validation-*
+  - split: challenge
+    path: quail/challenge-*
+  default: true
 ---
 
 # Dataset Card for "quail"

dataset_infos.json

@@ -1 +1,96 @@
-{"quail": {"description": "QuAIL is a  reading comprehension dataset. QuAIL contains 15K multi-choice questions in texts 300-350 tokens long 4 domains (news, user stories, fiction, blogs).QuAIL is balanced and annotated for question types.", "citation": "@inproceedings{DBLP:conf/aaai/RogersKDR20,\n  author    = {Anna Rogers and\n               Olga Kovaleva and\n               Matthew Downey and\n               Anna Rumshisky},\n  title     = {Getting Closer to {AI} Complete Question Answering: {A} Set of Prerequisite\n               Real Tasks},\n  booktitle = {The Thirty-Fourth {AAAI} Conference on Artificial Intelligence, {AAAI}\n               2020, The Thirty-Second Innovative Applications of Artificial Intelligence\n               Conference, {IAAI} 2020, The Tenth {AAAI} Symposium on Educational\n               Advances in Artificial Intelligence, {EAAI} 2020, New York, NY, USA,\n               February 7-12, 2020},\n  pages     = {8722--8731},\n  publisher = {{AAAI} Press},\n  year      = {2020},\n  url       = {https://aaai.org/ojs/index.php/AAAI/article/view/6398},\n  timestamp = {Thu, 04 Jun 2020 13:18:48 +0200},\n  biburl    = {https://dblp.org/rec/conf/aaai/RogersKDR20.bib},\n  bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n", "homepage": "https://text-machine-lab.github.io/blog/2020/quail/", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "context_id": {"dtype": "string", "id": null, "_type": "Value"}, "question_id": {"dtype": "string", "id": null, "_type": "Value"}, "domain": {"dtype": "string", "id": null, "_type": "Value"}, "metadata": {"author": {"dtype": "string", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}, "url": {"dtype": "string", "id": null, "_type": "Value"}}, "context": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "question_type": {"dtype": "string", "id": null, "_type": "Value"}, "answers": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "correct_answer_id": {"dtype": "int32", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "quail", "config_name": "quail", "version": {"version_str": "1.3.0", "description": "", "major": 1, "minor": 3, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 23432697, "num_examples": 10246, "dataset_name": "quail"}, "validation": {"name": "validation", "num_bytes": 4989579, "num_examples": 2164, "dataset_name": "quail"}, "challenge": {"name": "challenge", "num_bytes": 1199840, "num_examples": 556, "dataset_name": "quail"}}, "download_checksums": {"https://raw.githubusercontent.com/text-machine-lab/quail/master/quail_v1.3/xml/randomized/quail_1.3_train_randomized.xml": {"num_bytes": 5064067, "checksum": "faf7849a4397485fc6134919b9ce55e40ca623915be86bce16eccfb6c4186fac"}, "https://raw.githubusercontent.com/text-machine-lab/quail/master/quail_v1.3/xml/randomized/quail_1.3_dev_randomized.xml": {"num_bytes": 1075073, "checksum": "e39b848db1a13533ee264c9eaa21a309aebf3c0394967848acb89b83ae96b8c4"}, "https://raw.githubusercontent.com/text-machine-lab/quail/master/quail_v1.3/xml/randomized/quail_1.3_challenge_randomized.xml": {"num_bytes": 263793, "checksum": "1e140e6e6b9b820e70a75a79f8bc111db6472fd0027bbcfb760e6841045478ae"}}, "download_size": 6402933, "post_processing_size": null, "dataset_size": 29622116, "size_in_bytes": 36025049}}
+{
+    "quail": {
+        "description": "QuAIL is a  reading comprehension dataset. QuAIL contains 15K multi-choice questions in texts 300-350 tokens long 4 domains (news, user stories, fiction, blogs).QuAIL is balanced and annotated for question types.",
+        "citation": "@inproceedings{DBLP:conf/aaai/RogersKDR20,\n  author    = {Anna Rogers and\n               Olga Kovaleva and\n               Matthew Downey and\n               Anna Rumshisky},\n  title     = {Getting Closer to {AI} Complete Question Answering: {A} Set of Prerequisite\n               Real Tasks},\n  booktitle = {The Thirty-Fourth {AAAI} Conference on Artificial Intelligence, {AAAI}\n               2020, The Thirty-Second Innovative Applications of Artificial Intelligence\n               Conference, {IAAI} 2020, The Tenth {AAAI} Symposium on Educational\n               Advances in Artificial Intelligence, {EAAI} 2020, New York, NY, USA,\n               February 7-12, 2020},\n  pages     = {8722--8731},\n  publisher = {{AAAI} Press},\n  year      = {2020},\n  url       = {https://aaai.org/ojs/index.php/AAAI/article/view/6398},\n  timestamp = {Thu, 04 Jun 2020 13:18:48 +0200},\n  biburl    = {https://dblp.org/rec/conf/aaai/RogersKDR20.bib},\n  bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n",
+        "homepage": "https://text-machine-lab.github.io/blog/2020/quail/",
+        "license": "",
+        "features": {
+            "id": {
+                "dtype": "string",
+                "_type": "Value"
+            },
+            "context_id": {
+                "dtype": "string",
+                "_type": "Value"
+            },
+            "question_id": {
+                "dtype": "string",
+                "_type": "Value"
+            },
+            "domain": {
+                "dtype": "string",
+                "_type": "Value"
+            },
+            "metadata": {
+                "author": {
+                    "dtype": "string",
+                    "_type": "Value"
+                },
+                "title": {
+                    "dtype": "string",
+                    "_type": "Value"
+                },
+                "url": {
+                    "dtype": "string",
+                    "_type": "Value"
+                }
+            },
+            "context": {
+                "dtype": "string",
+                "_type": "Value"
+            },
+            "question": {
+                "dtype": "string",
+                "_type": "Value"
+            },
+            "question_type": {
+                "dtype": "string",
+                "_type": "Value"
+            },
+            "answers": {
+                "feature": {
+                    "dtype": "string",
+                    "_type": "Value"
+                },
+                "_type": "Sequence"
+            },
+            "correct_answer_id": {
+                "dtype": "int32",
+                "_type": "Value"
+            }
+        },
+        "builder_name": "quail",
+        "dataset_name": "quail",
+        "config_name": "quail",
+        "version": {
+            "version_str": "1.3.0",
+            "description": "",
+            "major": 1,
+            "minor": 3,
+            "patch": 0
+        },
+        "splits": {
+            "train": {
+                "name": "train",
+                "num_bytes": 23432601,
+                "num_examples": 10246,
+                "dataset_name": null
+            },
+            "validation": {
+                "name": "validation",
+                "num_bytes": 4989531,
+                "num_examples": 2164,
+                "dataset_name": null
+            },
+            "challenge": {
+                "name": "challenge",
+                "num_bytes": 1199792,
+                "num_examples": 556,
+                "dataset_name": null
+            }
+        },
+        "download_size": 2286403,
+        "dataset_size": 29621924,
+        "size_in_bytes": 31908327
+    }
+}

quail/challenge-00000-of-00001.parquet

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+size 96956

quail/train-00000-of-00001.parquet

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+oid sha256:e760cd0359e3aa59444bc8e551864d4fa518e06987380dabd50eed49179091ee
+size 1791229

quail/validation-00000-of-00001.parquet

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+oid sha256:b8ba2dd760c9c53a2642de0d8213ee66b6d252d5c279f0f0ac8e06602bf20bf1
+size 398218