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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 = 'istella22'
IRDS_ENTITY_TYPES = {'docs': {'doc_id': 'string', 'title': 'string', 'url': 'string', 'text': 'string', 'extra_text': 'string', 'lang': 'string', 'lang_pct': 'int64'}}
_CITATION = '@inproceedings{Dato2022Istella,\n title={The Istella22 Dataset: Bridging Traditional and Neural Learning to Rank Evaluation},\n author={Domenico Dato, Sean MacAvaney, Franco Maria Nardini, Raffaele Perego, Nicola Tonellotto},\n booktitle={Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval},\n year={2022}\n}'
_DESCRIPTION = "" # TODO
class istella22(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/istella22#istella22",
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)
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