Convert dataset to Parquet

README.md

@@ -35,6 +35,529 @@ language_bcp47:
 - es-ES
 - it-IT
 - fr-FR
+configs:
+- config_name: all
+  data_files:
+  - split: train
+    path: all/train-*
+  - split: validation
+    path: all/validation-*
+  - split: test
+    path: all/test-*
+- config_name: ar
+  data_files:
+  - split: train
+    path: ar/train-*
+  - split: validation
+    path: ar/validation-*
+  - split: test
+    path: ar/test-*
+- config_name: de
+  data_files:
+  - split: train
+    path: de/train-*
+  - split: validation
+    path: de/validation-*
+  - split: test
+    path: de/test-*
+- config_name: en
+  data_files:
+  - split: train
+    path: en/train-*
+  - split: validation
+    path: en/validation-*
+  - split: test
+    path: en/test-*
+  default: true
+- config_name: es
+  data_files:
+  - split: train
+    path: es/train-*
+  - split: validation
+    path: es/validation-*
+  - split: test
+    path: es/test-*
+- config_name: fr
+  data_files:
+  - split: train
+    path: fr/train-*
+  - split: validation
+    path: fr/validation-*
+  - split: test
+    path: fr/test-*
+- config_name: hi
+  data_files:
+  - split: train
+    path: hi/train-*
+  - split: validation
+    path: hi/validation-*
+  - split: test
+    path: hi/test-*
+- config_name: it
+  data_files:
+  - split: train
+    path: it/train-*
+  - split: validation
+    path: it/validation-*
+  - split: test
+    path: it/test-*
+- config_name: ja
+  data_files:
+  - split: train
+    path: ja/train-*
+  - split: validation
+    path: ja/validation-*
+  - split: test
+    path: ja/test-*
+- config_name: pt
+  data_files:
+  - split: train
+    path: pt/train-*
+  - split: validation
+    path: pt/validation-*
+  - split: test
+    path: pt/test-*
+dataset_info:
+- config_name: all
+  features:
+  - name: id
+    dtype: string
+  - name: lang
+    dtype: string
+  - name: question
+    dtype: string
+  - name: answerText
+    dtype: string
+  - name: category
+    dtype: string
+  - name: complexityType
+    dtype: string
+  - name: questionEntity
+    list:
+    - name: name
+      dtype: string
+    - name: entityType
+      dtype: string
+    - name: label
+      dtype: string
+    - name: mention
+      dtype: string
+    - name: span
+      list: int32
+  - name: answerEntity
+    list:
+    - name: name
+      dtype: string
+    - name: label
+      dtype: string
+  splits:
+  - name: train
+    num_bytes: 32617518
+    num_examples: 126000
+  - name: validation
+    num_bytes: 4693442
+    num_examples: 18000
+  - name: test
+    num_bytes: 9305705
+    num_examples: 36000
+  download_size: 17797002
+  dataset_size: 46616665
+- config_name: ar
+  features:
+  - name: id
+    dtype: string
+  - name: lang
+    dtype: string
+  - name: question
+    dtype: string
+  - name: answerText
+    dtype: string
+  - name: category
+    dtype: string
+  - name: complexityType
+    dtype: string
+  - name: questionEntity
+    list:
+    - name: name
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+    - name: entityType
+      dtype: string
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+    - name: mention
+      dtype: string
+    - name: span
+      list: int32
+  - name: answerEntity
+    list:
+    - name: name
+      dtype: string
+    - name: label
+      dtype: string
+  splits:
+  - name: train
+    num_bytes: 3880925
+    num_examples: 14000
+  - name: validation
+    num_bytes: 559451
+    num_examples: 2000
+  - name: test
+    num_bytes: 1105419
+    num_examples: 4000
+  download_size: 2073235
+  dataset_size: 5545795
+- config_name: de
+  features:
+  - name: id
+    dtype: string
+  - name: lang
+    dtype: string
+  - name: question
+    dtype: string
+  - name: answerText
+    dtype: string
+  - name: category
+    dtype: string
+  - name: complexityType
+    dtype: string
+  - name: questionEntity
+    list:
+    - name: name
+      dtype: string
+    - name: entityType
+      dtype: string
+    - name: label
+      dtype: string
+    - name: mention
+      dtype: string
+    - name: span
+      list: int32
+  - name: answerEntity
+    list:
+    - name: name
+      dtype: string
+    - name: label
+      dtype: string
+  splits:
+  - name: train
+    num_bytes: 3356063
+    num_examples: 14000
+  - name: validation
+    num_bytes: 481954
+    num_examples: 2000
+  - name: test
+    num_bytes: 956485
+    num_examples: 4000
+  download_size: 1897328
+  dataset_size: 4794502
+- config_name: en
+  features:
+  - name: id
+    dtype: string
+  - name: lang
+    dtype: string
+  - name: question
+    dtype: string
+  - name: answerText
+    dtype: string
+  - name: category
+    dtype: string
+  - name: complexityType
+    dtype: string
+  - name: questionEntity
+    list:
+    - name: name
+      dtype: string
+    - name: entityType
+      dtype: string
+    - name: label
+      dtype: string
+    - name: mention
+      dtype: string
+    - name: span
+      list: int32
+  - name: answerEntity
+    list:
+    - name: name
+      dtype: string
+    - name: label
+      dtype: string
+  splits:
+  - name: train
+    num_bytes: 3713651
+    num_examples: 14000
+  - name: validation
+    num_bytes: 533751
+    num_examples: 2000
+  - name: test
+    num_bytes: 1057790
+    num_examples: 4000
+  download_size: 2147987
+  dataset_size: 5305192
+- config_name: es
+  features:
+  - name: id
+    dtype: string
+  - name: lang
+    dtype: string
+  - name: question
+    dtype: string
+  - name: answerText
+    dtype: string
+  - name: category
+    dtype: string
+  - name: complexityType
+    dtype: string
+  - name: questionEntity
+    list:
+    - name: name
+      dtype: string
+    - name: entityType
+      dtype: string
+    - name: label
+      dtype: string
+    - name: mention
+      dtype: string
+    - name: span
+      list: int32
+  - name: answerEntity
+    list:
+    - name: name
+      dtype: string
+    - name: label
+      dtype: string
+  splits:
+  - name: train
+    num_bytes: 3370323
+    num_examples: 14000
+  - name: validation
+    num_bytes: 485203
+    num_examples: 2000
+  - name: test
+    num_bytes: 961828
+    num_examples: 4000
+  download_size: 1888205
+  dataset_size: 4817354
+- config_name: fr
+  features:
+  - name: id
+    dtype: string
+  - name: lang
+    dtype: string
+  - name: question
+    dtype: string
+  - name: answerText
+    dtype: string
+  - name: category
+    dtype: string
+  - name: complexityType
+    dtype: string
+  - name: questionEntity
+    list:
+    - name: name
+      dtype: string
+    - name: entityType
+      dtype: string
+    - name: label
+      dtype: string
+    - name: mention
+      dtype: string
+    - name: span
+      list: int32
+  - name: answerEntity
+    list:
+    - name: name
+      dtype: string
+    - name: label
+      dtype: string
+  splits:
+  - name: train
+    num_bytes: 3442616
+    num_examples: 14000
+  - name: validation
+    num_bytes: 494627
+    num_examples: 2000
+  - name: test
+    num_bytes: 981861
+    num_examples: 4000
+  download_size: 1928896
+  dataset_size: 4919104
+- config_name: hi
+  features:
+  - name: id
+    dtype: string
+  - name: lang
+    dtype: string
+  - name: question
+    dtype: string
+  - name: answerText
+    dtype: string
+  - name: category
+    dtype: string
+  - name: complexityType
+    dtype: string
+  - name: questionEntity
+    list:
+    - name: name
+      dtype: string
+    - name: entityType
+      dtype: string
+    - name: label
+      dtype: string
+    - name: mention
+      dtype: string
+    - name: span
+      list: int32
+  - name: answerEntity
+    list:
+    - name: name
+      dtype: string
+    - name: label
+      dtype: string
+  splits:
+  - name: train
+    num_bytes: 4491931
+    num_examples: 14000
+  - name: validation
+    num_bytes: 647607
+    num_examples: 2000
+  - name: test
+    num_bytes: 1282203
+    num_examples: 4000
+  download_size: 2176682
+  dataset_size: 6421741
+- config_name: it
+  features:
+  - name: id
+    dtype: string
+  - name: lang
+    dtype: string
+  - name: question
+    dtype: string
+  - name: answerText
+    dtype: string
+  - name: category
+    dtype: string
+  - name: complexityType
+    dtype: string
+  - name: questionEntity
+    list:
+    - name: name
+      dtype: string
+    - name: entityType
+      dtype: string
+    - name: label
+      dtype: string
+    - name: mention
+      dtype: string
+    - name: span
+      list: int32
+  - name: answerEntity
+    list:
+    - name: name
+      dtype: string
+    - name: label
+      dtype: string
+  splits:
+  - name: train
+    num_bytes: 3325824
+    num_examples: 14000
+  - name: validation
+    num_bytes: 478224
+    num_examples: 2000
+  - name: test
+    num_bytes: 950678
+    num_examples: 4000
+  download_size: 1881299
+  dataset_size: 4754726
+- config_name: ja
+  features:
+  - name: id
+    dtype: string
+  - name: lang
+    dtype: string
+  - name: question
+    dtype: string
+  - name: answerText
+    dtype: string
+  - name: category
+    dtype: string
+  - name: complexityType
+    dtype: string
+  - name: questionEntity
+    list:
+    - name: name
+      dtype: string
+    - name: entityType
+      dtype: string
+    - name: label
+      dtype: string
+    - name: mention
+      dtype: string
+    - name: span
+      list: int32
+  - name: answerEntity
+    list:
+    - name: name
+      dtype: string
+    - name: label
+      dtype: string
+  splits:
+  - name: train
+    num_bytes: 3753173
+    num_examples: 14000
+  - name: validation
+    num_bytes: 540236
+    num_examples: 2000
+  - name: test
+    num_bytes: 1072950
+    num_examples: 4000
+  download_size: 2032694
+  dataset_size: 5366359
+- config_name: pt
+  features:
+  - name: id
+    dtype: string
+  - name: lang
+    dtype: string
+  - name: question
+    dtype: string
+  - name: answerText
+    dtype: string
+  - name: category
+    dtype: string
+  - name: complexityType
+    dtype: string
+  - name: questionEntity
+    list:
+    - name: name
+      dtype: string
+    - name: entityType
+      dtype: string
+    - name: label
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+    - name: mention
+      dtype: string
+    - name: span
+      list: int32
+  - name: answerEntity
+    list:
+    - name: name
+      dtype: string
+    - name: label
+      dtype: string
+  splits:
+  - name: train
+    num_bytes: 3283012
+    num_examples: 14000
+  - name: validation
+    num_bytes: 472389
+    num_examples: 2000
+  - name: test
+    num_bytes: 936491
+    num_examples: 4000
+  download_size: 1851000
+  dataset_size: 4691892
 ---
 
 # Mintaka: A Complex, Natural, and Multilingual Dataset for End-to-End Question Answering

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mintaka.py

@@ -1,177 +0,0 @@
-# coding=utf-8
-
-"""Mintaka: A Complex, Natural, and Multilingual Dataset for End-to-End Question Answering"""
-
-import json
-import datasets
-
-logger = datasets.logging.get_logger(__name__)
-
-_DESCRIPTION = """\
-         Mintaka is a complex, natural, and multilingual dataset designed for experimenting with end-to-end
-         question-answering models. Mintaka is composed of 20,000 question-answer pairs collected in English,
-         annotated with Wikidata entities, and translated into Arabic, French, German, Hindi, Italian,
-         Japanese, Portuguese, and Spanish for a total of 180,000 samples.
-         Mintaka includes 8 types of complex questions, including superlative, intersection, and multi-hop questions, 
-         which were naturally elicited from crowd workers. 
-"""
-
-_CITATION = """\
-        @inproceedings{sen-etal-2022-mintaka,
-            title = "Mintaka: A Complex, Natural, and Multilingual Dataset for End-to-End Question Answering",
-            author = "Sen, Priyanka and Aji, Alham Fikri and Saffari, Amir",
-            booktitle = "Proceedings of the 29th International Conference on Computational Linguistics",
-            month = oct,
-            year = "2022",
-            address = "Gyeongju, Republic of Korea",
-            publisher = "International Committee on Computational Linguistics",
-            url = "https://aclanthology.org/2022.coling-1.138",
-            pages = "1604--1619"
-        }
-"""
-
-_LICENSE = """\
-Copyright Amazon.com Inc. or its affiliates.
-Attribution 4.0 International
-"""
-
-_TRAIN_URL = "https://raw.githubusercontent.com/amazon-science/mintaka/main/data/mintaka_train.json"
-_DEV_URL = "https://raw.githubusercontent.com/amazon-science/mintaka/main/data/mintaka_dev.json"
-_TEST_URL = "https://raw.githubusercontent.com/amazon-science/mintaka/main/data/mintaka_test.json"
-
-
-_LANGUAGES = ['en', 'ar', 'de', 'ja', 'hi', 'pt', 'es', 'it', 'fr']
-
-_ALL = "all"
-
-class Mintaka(datasets.GeneratorBasedBuilder):
-    """Mintaka: A Complex, Natural, and Multilingual Dataset for End-to-End Question Answering"""
-
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(
-            name = name,
-            version = datasets.Version("1.0.0"),
-            description = f"Mintaka: A Complex, Natural, and Multilingual Dataset for End-to-End Question Answering for {name}",
-        ) for name in _LANGUAGES
-    ]
-
-    BUILDER_CONFIGS.append(datasets.BuilderConfig(
-        name = _ALL,
-        version = datasets.Version("1.0.0"),
-        description = f"Mintaka: A Complex, Natural, and Multilingual Dataset for End-to-End Question Answering",
-    ))
-
-    DEFAULT_CONFIG_NAME = 'en'
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "id": datasets.Value("string"),
-                    "lang": datasets.Value("string"),
-                    "question": datasets.Value("string"),
-                    "answerText": datasets.Value("string"),
-                    "category": datasets.Value("string"),
-                    "complexityType": datasets.Value("string"),
-                    "questionEntity": [{
-                        "name": datasets.Value("string"),
-                        "entityType": datasets.Value("string"),
-                        "label": datasets.Value("string"),
-                        "mention": datasets.Value("string"),
-                        "span": [datasets.Value("int32")],
-                    }],
-                    "answerEntity": [{
-                        "name": datasets.Value("string"),
-                        "label": datasets.Value("string"),
-                    }]
-                },
-            ),
-            supervised_keys=None,
-            citation=_CITATION,
-            license=_LICENSE,
-        )
-
-    def _split_generators(self, dl_manager):
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "file": dl_manager.download_and_extract(_TRAIN_URL),
-                    "lang": self.config.name,
-                }
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={
-                    "file": dl_manager.download_and_extract(_DEV_URL),
-                    "lang": self.config.name,
-                }
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={
-                    "file": dl_manager.download_and_extract(_TEST_URL),
-                    "lang": self.config.name,
-                }
-            ),
-        ]
-
-    def _generate_examples(self, file, lang):
-        if lang == _ALL:
-            langs = _LANGUAGES
-        else:
-            langs = [lang]
-
-        key_ = 0
-
-        logger.info("⏳ Generating examples from = %s", ", ".join(lang))
-
-        with open(file, encoding='utf-8') as json_file:
-            data = json.load(json_file)
-            for lang in langs:
-                for sample in data:
-                    questionEntity = [
-                        {
-                            "name": str(qe["name"]),
-                            "entityType": qe["entityType"],
-                            "label": qe["label"] if "label" in qe else "",
-                            # span only applies for English question
-                            "mention": qe["mention"] if lang == "en" else None,
-                            "span": qe["span"] if lang == "en" else [],
-                        } for qe in sample["questionEntity"]
-                    ]
-
-                    answers = []
-                    if sample['answer']["answerType"] == "entity" and sample['answer']['answer'] is not None:
-                        answers = sample['answer']['answer']
-                    elif sample['answer']["answerType"] == "numerical" and "supportingEnt" in sample["answer"]:
-                        answers = sample['answer']['supportingEnt']
-
-                    # helper to get language for the corresponding language
-                    def get_label(labels, lang):
-                        if lang in labels:
-                            return labels[lang]
-                        if 'en' in labels:
-                            return labels['en']
-                        return None
-
-                    answerEntity = [
-                        {
-                            "name": str(ae["name"]),
-                            "label": get_label(ae["label"], lang),
-                        } for ae in answers
-                    ]
-
-                    yield key_, {
-                        "id": sample["id"],
-                        "lang": lang,
-                        "question": sample["question"] if lang == 'en' else sample['translations'][lang],
-                        "answerText": sample["answer"]["mention"],
-                        "category": sample["category"],
-                        "complexityType": sample["complexityType"],
-                        "questionEntity": questionEntity,
-                        "answerEntity": answerEntity,
-                    }
-
-                    key_ += 1

pt/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3d23837ade3cd345a1d41f1cb604829c2f88c3ac47a51880eb2b5c92ad0133fd
+size 399482

pt/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:58f0733590a97c1f5077f10122752afe6dd349180616c10e2dcb20a33bc267b5
+size 1236734

pt/validation-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:db3b749c095fb345c03d9cb4225e3bd6838ed9b52b63f58efe96ebe8ebe2d486
+size 214784

test_mintaka.py

@@ -1,16 +0,0 @@
-from datasets import load_dataset
-
-source = "AmazonScience/mintaka"
-
-#dataset = load_dataset(source, "all", download_mode="force_redownload")
-dataset = load_dataset(source, "all")
-
-print(dataset)
-print(dataset["train"][0])
-print(dataset["train"][0:10]['question'])
-
-
-dataset = load_dataset(source, "en")
-dataset = load_dataset(source, "ar")
-
-