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car.py
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car.py
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from typing import NamedTuple, Tuple
import ir_datasets
from ir_datasets.util import DownloadConfig, TarExtract, ReTar
from ir_datasets.formats import TrecQrels, BaseDocs, BaseQueries, GenericDoc
from ir_datasets.datasets.base import Dataset, YamlDocumentation
from ir_datasets.indices import PickleLz4FullStore
NAME = 'car'
AUTO_QRELS = {
1: 'Paragraph appears under heading'
}
MANUAL_QRELS = {
3: 'MUST be mentioned',
2: 'SHOULD be mentioned',
1: 'CAN be mentioned',
0: 'Non-relevant, but roughly on TOPIC',
-1: 'NO, non-relevant',
-2: 'Trash',
}
class CarQuery(NamedTuple):
query_id: str
text: str
title: str
headings: Tuple[str, ...]
class CarDocs(BaseDocs):
def __init__(self, streamer):
super().__init__()
self._streamer = streamer
@ir_datasets.util.use_docstore
def docs_iter(self):
trec_car = ir_datasets.lazy_libs.trec_car()
with self._streamer.stream() as stream:
paras = trec_car.read_data.iter_paragraphs(stream)
for p in paras:
yield GenericDoc(p.para_id, p.get_text())
def docs_cls(self):
return GenericDoc
def docs_store(self, field='doc_id'):
return PickleLz4FullStore(
path=f'{ir_datasets.util.home_path()/NAME}/docs.pklz4',
init_iter_fn=self.docs_iter,
data_cls=self.docs_cls(),
lookup_field=field,
index_fields=['doc_id'],
)
def docs_count(self):
return self.docs_store().count()
def docs_namespace(self):
return NAME
def docs_lang(self):
return 'en'
class CarQueries(BaseQueries):
def __init__(self, streamer):
super().__init__()
self._streamer = streamer
def queries_iter(self):
trec_car = ir_datasets.lazy_libs.trec_car()
with self._streamer.stream() as stream:
for page in trec_car.read_data.iter_outlines(stream):
for heads in page.flat_headings_list():
qid = '/'.join([page.page_id] + [h.headingId for h in heads])
title = page.page_name
headings = tuple(h.heading for h in heads)
text = ' '.join((title,) + headings)
yield CarQuery(qid, text, title, headings)
def queries_namespace(self):
return NAME
def queries_cls(self):
return CarQuery
def queries_lang(self):
return 'en'
def _init():
subsets = {}
base_path = ir_datasets.util.home_path()/NAME
dlc = DownloadConfig.context(NAME, base_path)
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
docs_v15 = CarDocs(TarExtract(dlc['docs'], 'paragraphcorpus/paragraphcorpus.cbor', compression='xz'))
base = Dataset(documentation('_'))
subsets['v1.5'] = Dataset(docs_v15, documentation('v1.5'))
subsets['v1.5/trec-y1'] = Dataset(
docs_v15,
CarQueries(TarExtract(dlc['trec-y1/queries'], 'benchmarkY1test.public/test.benchmarkY1test.cbor.outlines', compression='xz')),)
subsets['v1.5/trec-y1/manual'] = Dataset(
subsets['v1.5/trec-y1'],
TrecQrels(TarExtract(dlc['trec-y1/qrels'], 'TREC_CAR_2017_qrels/manual.benchmarkY1test.cbor.hierarchical.qrels'), MANUAL_QRELS))
subsets['v1.5/trec-y1/auto'] = Dataset(
subsets['v1.5/trec-y1'],
TrecQrels(TarExtract(dlc['trec-y1/qrels'], 'TREC_CAR_2017_qrels/automatic.benchmarkY1test.cbor.hierarchical.qrels'), AUTO_QRELS))
subsets['v1.5/test200'] = Dataset(
docs_v15,
CarQueries(TarExtract(dlc['test200'], 'test200/train.test200.cbor.outlines', compression='xz')),
TrecQrels(TarExtract(dlc['test200'], 'test200/train.test200.cbor.hierarchical.qrels', compression='xz'), AUTO_QRELS))
train_data = ReTar(dlc['train'], base_path/'train.smaller.tar.xz', ['train/train.fold?.cbor.outlines', 'train/train.fold?.cbor.hierarchical.qrels'], compression='xz')
subsets['v1.5/train/fold0'] = Dataset(
docs_v15,
CarQueries(TarExtract(train_data, 'train/train.fold0.cbor.outlines', compression='xz')),
TrecQrels(TarExtract(train_data, 'train/train.fold0.cbor.hierarchical.qrels', compression='xz'), AUTO_QRELS))
subsets['v1.5/train/fold1'] = Dataset(
docs_v15,
CarQueries(TarExtract(train_data, 'train/train.fold1.cbor.outlines', compression='xz')),
TrecQrels(TarExtract(train_data, 'train/train.fold1.cbor.hierarchical.qrels', compression='xz'), AUTO_QRELS))
subsets['v1.5/train/fold2'] = Dataset(
docs_v15,
CarQueries(TarExtract(train_data, 'train/train.fold2.cbor.outlines', compression='xz')),
TrecQrels(TarExtract(train_data, 'train/train.fold2.cbor.hierarchical.qrels', compression='xz'), AUTO_QRELS))
subsets['v1.5/train/fold3'] = Dataset(
docs_v15,
CarQueries(TarExtract(train_data, 'train/train.fold3.cbor.outlines', compression='xz')),
TrecQrels(TarExtract(train_data, 'train/train.fold3.cbor.hierarchical.qrels', compression='xz'), AUTO_QRELS))
subsets['v1.5/train/fold4'] = Dataset(
docs_v15,
CarQueries(TarExtract(train_data, 'train/train.fold4.cbor.outlines', compression='xz')),
TrecQrels(TarExtract(train_data, 'train/train.fold4.cbor.hierarchical.qrels', compression='xz'), AUTO_QRELS))
ir_datasets.registry.register(NAME, base)
for s in sorted(subsets):
ir_datasets.registry.register(f'{NAME}/{s}', Dataset(subsets[s], documentation(s)))
return base, subsets
base, subsets = _init()