| |
|
| | """ |
| | """ |
| | try: |
| | import ir_datasets |
| | except ImportError as e: |
| | raise ImportError('ir-datasets package missing; `pip install ir-datasets`') |
| | import datasets |
| |
|
| | IRDS_ID = 'mr-tydi/ar/dev' |
| | IRDS_ENTITY_TYPES = {'queries': {'query_id': 'string', 'text': 'string'}, 'qrels': {'query_id': 'string', 'doc_id': 'string', 'relevance': 'int64', 'iteration': 'string'}} |
| |
|
| | _CITATION = '@article{Zhang2021MrTyDi,\n title={{Mr. TyDi}: A Multi-lingual Benchmark for Dense Retrieval}, \n author={Xinyu Zhang and Xueguang Ma and Peng Shi and Jimmy Lin},\n year={2021},\n journal={arXiv:2108.08787},\n}\n@article{Clark2020TyDiQa,\n title={{TyDi QA}: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages},\n author={Jonathan H. Clark and Eunsol Choi and Michael Collins and Dan Garrette and Tom Kwiatkowski and Vitaly Nikolaev and Jennimaria Palomaki},\n year={2020},\n journal={Transactions of the Association for Computational Linguistics}\n}' |
| |
|
| | _DESCRIPTION = "" |
| |
|
| | class mr_tydi_ar_dev(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/mr-tydi#mr-tydi/ar/dev", |
| | 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 |
| | return super().as_dataset(split, *args, **kwargs) |
| |
|