Datasets:
Tasks:
Text Retrieval
Source Datasets:
irds/trec-robust04
""" | |
""" # TODO | |
try: | |
import ir_datasets | |
except ImportError as e: | |
raise ImportError('ir-datasets package missing; `pip install ir-datasets`') | |
import datasets | |
IRDS_ID = 'trec-robust04/fold3' | |
IRDS_ENTITY_TYPES = {'queries': {'query_id': 'string', 'text': 'string'}, 'qrels': {'query_id': 'string', 'doc_id': 'string', 'relevance': 'int64'}} | |
_CITATION = '@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 trec_robust04_fold3(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/trec-robust04#trec-robust04/fold3", | |
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) | |