Convert dataset to Parquet

Convert dataset to Parquet.

README.md

@@ -10,7 +10,6 @@ license:
 - unknown
 multilinguality:
 - monolingual
-pretty_name: OpenBookQA
 size_categories:
 - 1K<n<10K
 source_datasets:
@@ -20,8 +19,9 @@ task_categories:
 task_ids:
 - open-domain-qa
 paperswithcode_id: openbookqa
+pretty_name: OpenBookQA
 dataset_info:
-- config_name: main
+- config_name: additional
   features:
   - name: id
     dtype: string
@@ -35,19 +35,27 @@ dataset_info:
       dtype: string
   - name: answerKey
     dtype: string
+  - name: fact1
+    dtype: string
+  - name: humanScore
+    dtype: float32
+  - name: clarity
+    dtype: float32
+  - name: turkIdAnonymized
+    dtype: string
   splits:
   - name: train
-    num_bytes: 896034
+    num_bytes: 1290473
     num_examples: 4957
   - name: validation
-    num_bytes: 95519
+    num_bytes: 136141
     num_examples: 500
   - name: test
-    num_bytes: 91850
+    num_bytes: 130926
     num_examples: 500
   download_size: 1446098
-  dataset_size: 1083403
-- config_name: additional
+  dataset_size: 1557540
+- config_name: main
   features:
   - name: id
     dtype: string
@@ -61,26 +69,28 @@ dataset_info:
       dtype: string
   - name: answerKey
     dtype: string
-  - name: fact1
-    dtype: string
-  - name: humanScore
-    dtype: float32
-  - name: clarity
-    dtype: float32
-  - name: turkIdAnonymized
-    dtype: string
   splits:
   - name: train
-    num_bytes: 1290473
+    num_bytes: 895386
     num_examples: 4957
   - name: validation
-    num_bytes: 136141
+    num_bytes: 95428
     num_examples: 500
   - name: test
-    num_bytes: 130926
+    num_bytes: 91759
     num_examples: 500
-  download_size: 1446098
-  dataset_size: 1557540
+  download_size: 609613
+  dataset_size: 1082573
+configs:
+- config_name: main
+  data_files:
+  - split: train
+    path: main/train-*
+  - split: validation
+    path: main/validation-*
+  - split: test
+    path: main/test-*
+  default: true
 ---
 
 # Dataset Card for OpenBookQA

dataset_infos.json

@@ -1 +1,170 @@
-{"main": {"description": "OpenBookQA aims to promote research in advanced question-answering, probing a deeper understanding of both the topic\n(with salient facts summarized as an open book, also provided with the dataset) and the language it is expressed in. In\nparticular, it contains questions that require multi-step reasoning, use of additional common and commonsense knowledge,\nand rich text comprehension.\nOpenBookQA is a new kind of question-answering dataset modeled after open book exams for assessing human understanding\nof a subject.\n", "citation": "@inproceedings{OpenBookQA2018,\n title={Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering},\n author={Todor Mihaylov and Peter Clark and Tushar Khot and Ashish Sabharwal},\n booktitle={EMNLP},\n year={2018}\n}\n", "homepage": "https://allenai.org/data/open-book-qa", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "question_stem": {"dtype": "string", "id": null, "_type": "Value"}, "choices": {"feature": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "answerKey": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "openbookqa", "config_name": "main", "version": {"version_str": "1.0.1", "description": "", "major": 1, "minor": 0, "patch": 1}, "splits": {"train": {"name": "train", "num_bytes": 896034, "num_examples": 4957, "dataset_name": "openbookqa"}, "validation": {"name": "validation", "num_bytes": 95519, "num_examples": 500, "dataset_name": "openbookqa"}, "test": {"name": "test", "num_bytes": 91850, "num_examples": 500, "dataset_name": "openbookqa"}}, "download_checksums": {"https://s3-us-west-2.amazonaws.com/ai2-website/data/OpenBookQA-V1-Sep2018.zip": {"num_bytes": 1446098, "checksum": "82368cf05df2e3b309c17d162e10b888b4d768fad6e171e0a041954c8553be46"}}, "download_size": 1446098, "post_processing_size": null, "dataset_size": 1083403, "size_in_bytes": 2529501}, "additional": {"description": "OpenBookQA aims to promote research in advanced question-answering, probing a deeper understanding of both the topic\n(with salient facts summarized as an open book, also provided with the dataset) and the language it is expressed in. In\nparticular, it contains questions that require multi-step reasoning, use of additional common and commonsense knowledge,\nand rich text comprehension.\nOpenBookQA is a new kind of question-answering dataset modeled after open book exams for assessing human understanding\nof a subject.\n", "citation": "@inproceedings{OpenBookQA2018,\n title={Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering},\n author={Todor Mihaylov and Peter Clark and Tushar Khot and Ashish Sabharwal},\n booktitle={EMNLP},\n year={2018}\n}\n", "homepage": "https://allenai.org/data/open-book-qa", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "question_stem": {"dtype": "string", "id": null, "_type": "Value"}, "choices": {"feature": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "answerKey": {"dtype": "string", "id": null, "_type": "Value"}, "fact1": {"dtype": "string", "id": null, "_type": "Value"}, "humanScore": {"dtype": "float32", "id": null, "_type": "Value"}, "clarity": {"dtype": "float32", "id": null, "_type": "Value"}, "turkIdAnonymized": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "openbookqa", "config_name": "additional", "version": {"version_str": "1.0.1", "description": "", "major": 1, "minor": 0, "patch": 1}, "splits": {"train": {"name": "train", "num_bytes": 1290473, "num_examples": 4957, "dataset_name": "openbookqa"}, "validation": {"name": "validation", "num_bytes": 136141, "num_examples": 500, "dataset_name": "openbookqa"}, "test": {"name": "test", "num_bytes": 130926, "num_examples": 500, "dataset_name": "openbookqa"}}, "download_checksums": {"https://s3-us-west-2.amazonaws.com/ai2-website/data/OpenBookQA-V1-Sep2018.zip": {"num_bytes": 1446098, "checksum": "82368cf05df2e3b309c17d162e10b888b4d768fad6e171e0a041954c8553be46"}}, "download_size": 1446098, "post_processing_size": null, "dataset_size": 1557540, "size_in_bytes": 3003638}}
+{
+    "main": {
+        "description": "OpenBookQA aims to promote research in advanced question-answering, probing a deeper understanding of both the topic\n(with salient facts summarized as an open book, also provided with the dataset) and the language it is expressed in. In\nparticular, it contains questions that require multi-step reasoning, use of additional common and commonsense knowledge,\nand rich text comprehension.\nOpenBookQA is a new kind of question-answering dataset modeled after open book exams for assessing human understanding\nof a subject.\n",
+        "citation": "@inproceedings{OpenBookQA2018,\n title={Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering},\n author={Todor Mihaylov and Peter Clark and Tushar Khot and Ashish Sabharwal},\n booktitle={EMNLP},\n year={2018}\n}\n",
+        "homepage": "https://allenai.org/data/open-book-qa",
+        "license": "",
+        "features": {
+            "id": {
+                "dtype": "string",
+                "_type": "Value"
+            },
+            "question_stem": {
+                "dtype": "string",
+                "_type": "Value"
+            },
+            "choices": {
+                "feature": {
+                    "text": {
+                        "dtype": "string",
+                        "_type": "Value"
+                    },
+                    "label": {
+                        "dtype": "string",
+                        "_type": "Value"
+                    }
+                },
+                "_type": "Sequence"
+            },
+            "answerKey": {
+                "dtype": "string",
+                "_type": "Value"
+            }
+        },
+        "builder_name": "openbookqa",
+        "dataset_name": "openbookqa",
+        "config_name": "main",
+        "version": {
+            "version_str": "1.0.1",
+            "description": "",
+            "major": 1,
+            "minor": 0,
+            "patch": 1
+        },
+        "splits": {
+            "train": {
+                "name": "train",
+                "num_bytes": 895386,
+                "num_examples": 4957,
+                "dataset_name": null
+            },
+            "validation": {
+                "name": "validation",
+                "num_bytes": 95428,
+                "num_examples": 500,
+                "dataset_name": null
+            },
+            "test": {
+                "name": "test",
+                "num_bytes": 91759,
+                "num_examples": 500,
+                "dataset_name": null
+            }
+        },
+        "download_size": 609613,
+        "dataset_size": 1082573,
+        "size_in_bytes": 1692186
+    },
+    "additional": {
+        "description": "OpenBookQA aims to promote research in advanced question-answering, probing a deeper understanding of both the topic\n(with salient facts summarized as an open book, also provided with the dataset) and the language it is expressed in. In\nparticular, it contains questions that require multi-step reasoning, use of additional common and commonsense knowledge,\nand rich text comprehension.\nOpenBookQA is a new kind of question-answering dataset modeled after open book exams for assessing human understanding\nof a subject.\n",
+        "citation": "@inproceedings{OpenBookQA2018,\n title={Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering},\n author={Todor Mihaylov and Peter Clark and Tushar Khot and Ashish Sabharwal},\n booktitle={EMNLP},\n year={2018}\n}\n",
+        "homepage": "https://allenai.org/data/open-book-qa",
+        "license": "",
+        "features": {
+            "id": {
+                "dtype": "string",
+                "id": null,
+                "_type": "Value"
+            },
+            "question_stem": {
+                "dtype": "string",
+                "id": null,
+                "_type": "Value"
+            },
+            "choices": {
+                "feature": {
+                    "text": {
+                        "dtype": "string",
+                        "id": null,
+                        "_type": "Value"
+                    },
+                    "label": {
+                        "dtype": "string",
+                        "id": null,
+                        "_type": "Value"
+                    }
+                },
+                "length": -1,
+                "id": null,
+                "_type": "Sequence"
+            },
+            "answerKey": {
+                "dtype": "string",
+                "id": null,
+                "_type": "Value"
+            },
+            "fact1": {
+                "dtype": "string",
+                "id": null,
+                "_type": "Value"
+            },
+            "humanScore": {
+                "dtype": "float32",
+                "id": null,
+                "_type": "Value"
+            },
+            "clarity": {
+                "dtype": "float32",
+                "id": null,
+                "_type": "Value"
+            },
+            "turkIdAnonymized": {
+                "dtype": "string",
+                "id": null,
+                "_type": "Value"
+            }
+        },
+        "post_processed": null,
+        "supervised_keys": null,
+        "task_templates": null,
+        "builder_name": "openbookqa",
+        "config_name": "additional",
+        "version": {
+            "version_str": "1.0.1",
+            "description": "",
+            "major": 1,
+            "minor": 0,
+            "patch": 1
+        },
+        "splits": {
+            "train": {
+                "name": "train",
+                "num_bytes": 1290473,
+                "num_examples": 4957,
+                "dataset_name": "openbookqa"
+            },
+            "validation": {
+                "name": "validation",
+                "num_bytes": 136141,
+                "num_examples": 500,
+                "dataset_name": "openbookqa"
+            },
+            "test": {
+                "name": "test",
+                "num_bytes": 130926,
+                "num_examples": 500,
+                "dataset_name": "openbookqa"
+            }
+        },
+        "download_checksums": {
+            "https://s3-us-west-2.amazonaws.com/ai2-website/data/OpenBookQA-V1-Sep2018.zip": {
+                "num_bytes": 1446098,
+                "checksum": "82368cf05df2e3b309c17d162e10b888b4d768fad6e171e0a041954c8553be46"
+            }
+        },
+        "download_size": 1446098,
+        "post_processing_size": null,
+        "dataset_size": 1557540,
+        "size_in_bytes": 3003638
+    }
+}

main/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
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+size 55535

main/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
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+size 495845

main/validation-00000-of-00001.parquet

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+size 58233