commit files to HF hub

README.md

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+---
+pretty_name: '`cord19/trec-covid/round1`'
+viewer: false
+source_datasets: []
+task_categories:
+- text-retrieval
+---
+
+# Dataset Card for `cord19/trec-covid/round1`
+
+The `cord19/trec-covid/round1` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
+For more information about the dataset, see the [documentation](https://ir-datasets.com/cord19#cord19/trec-covid/round1).
+
+# Data
+
+This dataset provides:
+ - `docs` (documents, i.e., the corpus); count=51,078
+ - `queries` (i.e., topics); count=30
+ - `qrels`: (relevance assessments); count=8,691
+
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+docs = load_dataset('irds/cord19_trec-covid_round1', 'docs')
+for record in docs:
+    record # {'doc_id': ..., 'title': ..., 'doi': ..., 'date': ..., 'abstract': ...}
+
+queries = load_dataset('irds/cord19_trec-covid_round1', 'queries')
+for record in queries:
+    record # {'query_id': ..., 'title': ..., 'description': ..., 'narrative': ...}
+
+qrels = load_dataset('irds/cord19_trec-covid_round1', '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
+
+```
+@article{Voorhees2020TrecCovid,
+  title={TREC-COVID: Constructing a Pandemic Information Retrieval Test Collection},
+  author={E. Voorhees and Tasmeer Alam and Steven Bedrick and Dina Demner-Fushman and W. Hersh and Kyle Lo and Kirk Roberts and I. Soboroff and Lucy Lu Wang},
+  journal={ArXiv},
+  year={2020},
+  volume={abs/2005.04474}
+}
+@article{Wang2020Cord19,
+  title={CORD-19: The Covid-19 Open Research Dataset},
+  author={Lucy Lu Wang and Kyle Lo and Yoganand Chandrasekhar and Russell Reas and Jiangjiang Yang and Darrin Eide and K. Funk and Rodney Michael Kinney and Ziyang Liu and W. Merrill and P. Mooney and D. Murdick and Devvret Rishi and Jerry Sheehan and Zhihong Shen and B. Stilson and A. Wade and K. Wang and Christopher Wilhelm and Boya Xie and D. Raymond and Daniel S. Weld and Oren Etzioni and Sebastian Kohlmeier},
+  journal={ArXiv},
+  year={2020}
+}
+```

cord19_trec-covid_round1.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 = 'cord19/trec-covid/round1'
+IRDS_ENTITY_TYPES = {'docs': {'doc_id': 'string', 'title': 'string', 'doi': 'string', 'date': 'string', 'abstract': 'string'}, 'queries': {'query_id': 'string', 'title': 'string', 'description': 'string', 'narrative': 'string'}, 'qrels': {'query_id': 'string', 'doc_id': 'string', 'relevance': 'int64', 'iteration': 'string'}}
+
+_CITATION = '@article{Voorhees2020TrecCovid,\n  title={TREC-COVID: Constructing a Pandemic Information Retrieval Test Collection},\n  author={E. Voorhees and Tasmeer Alam and Steven Bedrick and Dina Demner-Fushman and W. Hersh and Kyle Lo and Kirk Roberts and I. Soboroff and Lucy Lu Wang},\n  journal={ArXiv},\n  year={2020},\n  volume={abs/2005.04474}\n}\n@article{Wang2020Cord19,\n  title={CORD-19: The Covid-19 Open Research Dataset},\n  author={Lucy Lu Wang and Kyle Lo and Yoganand Chandrasekhar and Russell Reas and Jiangjiang Yang and Darrin Eide and K. Funk and Rodney Michael Kinney and Ziyang Liu and W. Merrill and P. Mooney and D. Murdick and Devvret Rishi and Jerry Sheehan and Zhihong Shen and B. Stilson and A. Wade and K. Wang and Christopher Wilhelm and Boya Xie and D. Raymond and Daniel S. Weld and Oren Etzioni and Sebastian Kohlmeier},\n  journal={ArXiv},\n  year={2020}\n}'
+
+_DESCRIPTION = "" # TODO
+
+class cord19_trec_covid_round1(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/cord19#cord19/trec-covid/round1",
+            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)