commit files to HF hub

README.md

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+---
+pretty_name: '`disks45/nocr/trec-robust-2004`'
+viewer: false
+source_datasets: ['irds/disks45_nocr']
+task_categories:
+- text-retrieval
+---
+
+# Dataset Card for `disks45/nocr/trec-robust-2004`
+
+The `disks45/nocr/trec-robust-2004` 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/trec-robust-2004).
+
+# Data
+
+This dataset provides:
+ - `queries` (i.e., topics); count=250
+ - `qrels`: (relevance assessments); count=311,410
+
+ - For `docs`, use [`irds/disks45_nocr`](https://huggingface.co/datasets/irds/disks45_nocr)
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+queries = load_dataset('irds/disks45_nocr_trec-robust-2004', 'queries')
+for record in queries:
+    record # {'query_id': ..., 'title': ..., 'description': ..., 'narrative': ...}
+
+qrels = load_dataset('irds/disks45_nocr_trec-robust-2004', 'qrels')
+for record in qrels:
+    record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
+
+```
+
+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}
+}
+@inproceedings{Voorhees2004Robust,
+  title={Overview of the TREC 2004 Robust Retrieval Track},
+  author={Ellen Voorhees},
+  booktitle={TREC},
+  year={2004}
+}
+@inproceedings{Huston2014ACO,
+  title={A Comparison of Retrieval Models using Term Dependencies},
+  author={Samuel Huston and W. Bruce Croft},
+  booktitle={CIKM},
+  year={2014}
+}
+```

disks45_nocr_trec-robust-2004.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/trec-robust-2004'
+IRDS_ENTITY_TYPES = {'queries': {'query_id': 'string', 'title': 'string', 'description': 'string', 'narrative': 'string'}, 'qrels': {'query_id': 'string', 'doc_id': 'string', 'relevance': 'int64', 'iteration': 'string'}}
+
+_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}\n@inproceedings{Voorhees2004Robust,\n  title={Overview of the TREC 2004 Robust Retrieval Track},\n  author={Ellen Voorhees},\n  booktitle={TREC},\n  year={2004}\n}\n@inproceedings{Huston2014ACO,\n  title={A Comparison of Retrieval Models using Term Dependencies},\n  author={Samuel Huston and W. Bruce Croft},\n  booktitle={CIKM},\n  year={2014}\n}'
+
+_DESCRIPTION = "" # TODO
+
+class disks45_nocr_trec_robust_2004(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/trec-robust-2004",
+            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)