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README.md

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+---
+pretty_name: '`disks45/nocr`'
+viewer: false
+source_datasets: []
+task_categories:
+- text-retrieval
+---
+
+# Dataset Card for `disks45/nocr`
+
+The `disks45/nocr` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
+For more information about the dataset, see the [documentation](https://ir-datasets.com/disks45#disks45/nocr).
+
+# Data
+
+This dataset provides:
+ - `docs` (documents, i.e., the corpus); count=528,155
+
+
+This dataset is used by: [`disks45_nocr_trec-robust-2004`](https://huggingface.co/datasets/irds/disks45_nocr_trec-robust-2004), [`disks45_nocr_trec-robust-2004_fold1`](https://huggingface.co/datasets/irds/disks45_nocr_trec-robust-2004_fold1), [`disks45_nocr_trec-robust-2004_fold2`](https://huggingface.co/datasets/irds/disks45_nocr_trec-robust-2004_fold2), [`disks45_nocr_trec-robust-2004_fold3`](https://huggingface.co/datasets/irds/disks45_nocr_trec-robust-2004_fold3), [`disks45_nocr_trec-robust-2004_fold4`](https://huggingface.co/datasets/irds/disks45_nocr_trec-robust-2004_fold4), [`disks45_nocr_trec-robust-2004_fold5`](https://huggingface.co/datasets/irds/disks45_nocr_trec-robust-2004_fold5), [`disks45_nocr_trec7`](https://huggingface.co/datasets/irds/disks45_nocr_trec7), [`disks45_nocr_trec8`](https://huggingface.co/datasets/irds/disks45_nocr_trec8)
+
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+docs = load_dataset('irds/disks45_nocr', 'docs')
+for record in docs:
+    record # {'doc_id': ..., 'title': ..., 'body': ..., 'marked_up_doc': ...}
+
+```
+
+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
+
+```
+@misc{Voorhees1996Disks45,
+  title = {NIST TREC Disks 4 and 5: Retrieval Test Collections Document Set},
+  author = {Ellen M. Voorhees},
+  doi = {10.18434/t47g6m},
+  year = {1996},
+  publisher = {National Institute of Standards and Technology}
+}
+```

disks45_nocr.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 = 'disks45/nocr'
+IRDS_ENTITY_TYPES = {'docs': {'doc_id': 'string', 'title': 'string', 'body': 'string', 'marked_up_doc': 'binary'}}
+
+_CITATION = '@misc{Voorhees1996Disks45,\n  title = {NIST TREC Disks 4 and 5: Retrieval Test Collections Document Set},\n  author = {Ellen M. Voorhees},\n  doi = {10.18434/t47g6m},\n  year = {1996},\n  publisher = {National Institute of Standards and Technology}\n}'
+
+_DESCRIPTION = "" # TODO
+
+class disks45_nocr(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/disks45#disks45/nocr",
+            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)