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  1. README.md +63 -0
  2. wikiclir_vi.py +43 -0
README.md ADDED
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+ ---
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+ pretty_name: '`wikiclir/vi`'
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+ viewer: false
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+ source_datasets: []
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+ task_categories:
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+ - text-retrieval
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+ ---
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+
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+ # Dataset Card for `wikiclir/vi`
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+
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+ The `wikiclir/vi` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
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+ For more information about the dataset, see the [documentation](https://ir-datasets.com/wikiclir#wikiclir/vi).
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+
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+ # Data
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+
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+ This dataset provides:
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+ - `docs` (documents, i.e., the corpus); count=1,392,152
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+ - `queries` (i.e., topics); count=354,312
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+ - `qrels`: (relevance assessments); count=611,355
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+
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+
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+ ## Usage
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ docs = load_dataset('irds/wikiclir_vi', 'docs')
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+ for record in docs:
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+ record # {'doc_id': ..., 'title': ..., 'text': ...}
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+
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+ queries = load_dataset('irds/wikiclir_vi', 'queries')
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+ for record in queries:
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+ record # {'query_id': ..., 'text': ...}
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+
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+ qrels = load_dataset('irds/wikiclir_vi', 'qrels')
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+ for record in qrels:
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+ record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
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+
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+ ```
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+
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+ Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
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+ data in 🤗 Dataset format.
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+
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+ ## Citation Information
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+
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+ ```
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+ @inproceedings{sasaki-etal-2018-cross,
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+ title = "Cross-Lingual Learning-to-Rank with Shared Representations",
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+ author = "Sasaki, Shota and
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+ Sun, Shuo and
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+ Schamoni, Shigehiko and
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+ Duh, Kevin and
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+ Inui, Kentaro",
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+ booktitle = "Proceedings of the 2018 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)",
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+ month = jun,
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+ year = "2018",
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+ address = "New Orleans, Louisiana",
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+ publisher = "Association for Computational Linguistics",
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+ url = "https://aclanthology.org/N18-2073",
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+ doi = "10.18653/v1/N18-2073",
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+ pages = "458--463"
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+ }
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+ ```
wikiclir_vi.py ADDED
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+
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+ """
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+ """ # TODO
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+ try:
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+ import ir_datasets
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+ except ImportError as e:
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+ raise ImportError('ir-datasets package missing; `pip install ir-datasets`')
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+ import datasets
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+
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+ IRDS_ID = 'wikiclir/vi'
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+ IRDS_ENTITY_TYPES = {'docs': {'doc_id': 'string', 'title': 'string', 'text': 'string'}, 'queries': {'query_id': 'string', 'text': 'string'}, 'qrels': {'query_id': 'string', 'doc_id': 'string', 'relevance': 'int64', 'iteration': 'string'}}
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+
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+ _CITATION = '@inproceedings{sasaki-etal-2018-cross,\n title = "Cross-Lingual Learning-to-Rank with Shared Representations",\n author = "Sasaki, Shota and\n Sun, Shuo and\n Schamoni, Shigehiko and\n Duh, Kevin and\n Inui, Kentaro",\n booktitle = "Proceedings of the 2018 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)",\n month = jun,\n year = "2018",\n address = "New Orleans, Louisiana",\n publisher = "Association for Computational Linguistics",\n url = "https://aclanthology.org/N18-2073",\n doi = "10.18653/v1/N18-2073",\n pages = "458--463"\n}'
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+
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+ _DESCRIPTION = "" # TODO
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+
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+ class wikiclir_vi(datasets.GeneratorBasedBuilder):
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+ BUILDER_CONFIGS = [datasets.BuilderConfig(name=e) for e in IRDS_ENTITY_TYPES]
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+
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+ def _info(self):
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+ return datasets.DatasetInfo(
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+ description=_DESCRIPTION,
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+ features=datasets.Features({k: datasets.Value(v) for k, v in IRDS_ENTITY_TYPES[self.config.name].items()}),
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+ homepage=f"https://ir-datasets.com/wikiclir#wikiclir/vi",
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+ citation=_CITATION,
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+ )
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+
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+ def _split_generators(self, dl_manager):
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+ return [datasets.SplitGenerator(name=self.config.name)]
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+
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+ def _generate_examples(self):
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+ dataset = ir_datasets.load(IRDS_ID)
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+ for i, item in enumerate(getattr(dataset, self.config.name)):
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+ key = i
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+ if self.config.name == 'docs':
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+ key = item.doc_id
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+ elif self.config.name == 'queries':
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+ key = item.query_id
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+ yield key, item._asdict()
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+
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+ def as_dataset(self, split=None, *args, **kwargs):
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+ split = self.config.name # always return split corresponding with this config to avid returning a redundant DatasetDict layer
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+ return super().as_dataset(split, *args, **kwargs)