commit files to HF hub

README.md

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+---
+pretty_name: '`natural-questions`'
+viewer: false
+source_datasets: []
+task_categories:
+- text-retrieval
+---
+
+# Dataset Card for `natural-questions`
+
+The `natural-questions` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
+For more information about the dataset, see the [documentation](https://ir-datasets.com/natural-questions#natural-questions).
+
+# Data
+
+This dataset provides:
+ - `docs` (documents, i.e., the corpus); count=28,390,850
+
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+docs = load_dataset('irds/natural-questions', 'docs')
+for record in docs:
+    record # {'doc_id': ..., 'text': ..., 'html': ..., 'start_byte': ..., 'end_byte': ..., 'start_token': ..., 'end_token': ..., 'document_title': ..., 'document_url': ..., 'parent_doc_id': ...}
+
+```
+
+Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
+data in 🤗 Dataset format.
+
+## Citation Information
+
+```
+@article{Kwiatkowski2019Nq,
+  title = {Natural Questions: a Benchmark for Question Answering Research},
+  author = {Tom Kwiatkowski and Jennimaria Palomaki and Olivia Redfield and Michael Collins and Ankur Parikh and Chris Alberti and Danielle Epstein and Illia Polosukhin and Matthew Kelcey and Jacob Devlin and Kenton Lee and Kristina N. Toutanova and Llion Jones and Ming-Wei Chang and Andrew Dai and Jakob Uszkoreit and Quoc Le and Slav Petrov},
+  year = {2019},
+  journal = {TACL}
+}
+```

natural-questions.py

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+
+"""
+""" # TODO
+try:
+    import ir_datasets
+except ImportError as e:
+    raise ImportError('ir-datasets package missing; `pip install ir-datasets`')
+import datasets
+
+IRDS_ID = 'natural-questions'
+IRDS_ENTITY_TYPES = {'docs': {'doc_id': 'string', 'text': 'string', 'html': 'string', 'start_byte': 'int64', 'end_byte': 'int64', 'start_token': 'int64', 'end_token': 'int64', 'document_title': 'string', 'document_url': 'string', 'parent_doc_id': 'string'}}
+
+_CITATION = '@article{Kwiatkowski2019Nq,\n  title = {Natural Questions: a Benchmark for Question Answering Research},\n  author = {Tom Kwiatkowski and Jennimaria Palomaki and Olivia Redfield and Michael Collins and Ankur Parikh and Chris Alberti and Danielle Epstein and Illia Polosukhin and Matthew Kelcey and Jacob Devlin and Kenton Lee and Kristina N. Toutanova and Llion Jones and Ming-Wei Chang and Andrew Dai and Jakob Uszkoreit and Quoc Le and Slav Petrov},\n  year = {2019},\n  journal = {TACL}\n}'
+
+_DESCRIPTION = "" # TODO
+
+class natural_questions(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [datasets.BuilderConfig(name=e) for e in IRDS_ENTITY_TYPES]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features({k: datasets.Value(v) for k, v in IRDS_ENTITY_TYPES[self.config.name].items()}),
+            homepage=f"https://ir-datasets.com/natural-questions#natural-questions",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        return [datasets.SplitGenerator(name=self.config.name)]
+
+    def _generate_examples(self):
+        dataset = ir_datasets.load(IRDS_ID)
+        for i, item in enumerate(getattr(dataset, self.config.name)):
+            key = i
+            if self.config.name == 'docs':
+                key = item.doc_id
+            elif self.config.name == 'queries':
+                key = item.query_id
+            yield key, item._asdict()
+
+    def as_dataset(self, split=None, *args, **kwargs):
+        split = self.config.name # always return split corresponding with this config to avid returning a redundant DatasetDict layer
+        return super().as_dataset(split, *args, **kwargs)