def _init():
subsets = {}
base_path = ir_datasets.util.home_path() / NAME
dlc = DownloadConfig.context(NAME, base_path)
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
collection = TrecDocs(dlc['docs'],
encoding='utf8',
path_globs=[
'aquaint_comp/apw/*/*.gz',
'aquaint_comp/nyt/*/*.gz',
'aquaint_comp/xie/*/*.gz'
],
namespace=NAME,
lang='en',
count_hint=ir_datasets.util.count_hint(NAME))
base = Dataset(collection, documentation('_'))
subsets['trec-robust-2005'] = Dataset(
TrecQueries(dlc['trec-robust-2005/queries'],
qtype_map=QTYPE_MAP,
namespace='trec-robust',
lang='en'),
TrecQrels(dlc['trec-robust-2005/qrels'], QREL_DEFS), collection,
documentation('trec-robust-2005'))
ir_datasets.registry.register(NAME, base)
for s in sorted(subsets):
ir_datasets.registry.register(f'{NAME}/{s}', subsets[s])
return base, subsets
def _init():
subsets = {}
base_path = ir_datasets.util.home_path() / NAME
dlc = DownloadConfig.context(NAME, base_path)
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
collection = TrecDocs(
dlc['docs'],
encoding='utf8',
path_globs=['arabic_newswire_a/transcripts/*/*.sgm.gz'],
namespace=NAME)
base = Dataset(collection, documentation('_'))
subsets['ar2001'] = Dataset(
TrecQueries(dlc['ar2001/queries'],
qtype_map=QTYPE_MAP,
encoding='ISO-8859-6',
namespace=NAME), TrecQrels(dlc['ar2001/qrels'], QREL_DEFS),
collection, documentation('ar2001'))
subsets['ar2002'] = Dataset(
TrecQueries(dlc['ar2002/queries'],
qtype_map=QTYPE_MAP,
encoding='ISO-8859-6',
namespace=NAME), TrecQrels(dlc['ar2002/qrels'], QREL_DEFS),
collection, documentation('ar2002'))
ir_datasets.registry.register(NAME, base)
for s in sorted(subsets):
ir_datasets.registry.register(f'{NAME}/{s}', subsets[s])
return base, subsets
def _init():
subsets = {}
base_path = ir_datasets.util.home_path() / NAME
dlc = DownloadConfig.context(NAME, base_path)
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
en_noclean_tr_collection = C4Docs(
GzipExtract(dlc['en-noclean/sources']),
TarExtractAll(dlc['en-noclean/checkpoints'],
base_path / 'en.noclean.checkpoints'),
base_path,
source_name_filter=r'en\.noclean\.c4-train',
filter_name='train') # exclude validation files (only include train)
base = Dataset(documentation('_'))
subsets['en-noclean-tr'] = Dataset(en_noclean_tr_collection,
documentation('en-noclean-tr'))
subsets['en-noclean-tr/trec-misinfo-2021'] = Dataset(
en_noclean_tr_collection,
TrecXmlQueries(dlc['trec-misinfo-2021/queries'],
qtype=MisinfoQuery,
qtype_map=misinfo_map,
namespace='trec-misinfo',
lang='en'),
documentation('en-noclean-tr/trec-misinfo-2021'))
ir_datasets.registry.register(NAME, base)
for subset in subsets:
ir_datasets.registry.register(f'{NAME}/{subset}', subsets[subset])
return base, subsets
def _init():
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
base_path = ir_datasets.util.home_path() / NAME
dlc = DownloadConfig.context(NAME, base_path)
subsets = {}
collection = HighwireDocs(dlc, dlc['legalspans'])
base = Dataset(collection, documentation('_'))
subsets['trec-genomics-2006'] = Dataset(
collection,
TrecGenomicsQueries(dlc['trec-genomics-2006/queries']),
HighwireQrels(dlc['trec-genomics-2006/qrels'], QREL_DEFS_06),
documentation('trec-genomics-2006'),
)
subsets['trec-genomics-2007'] = Dataset(
collection,
TrecGenomicsQueries(dlc['trec-genomics-2007/queries']),
HighwireQrels(dlc['trec-genomics-2007/qrels'], QREL_DEFS_07),
documentation('trec-genomics-2007'),
)
ir_datasets.registry.register(NAME, base)
for s in sorted(subsets):
ir_datasets.registry.register(f'{NAME}/{s}', subsets[s])
return base, subsets
def _init():
base_path = ir_datasets.util.home_path()/NAME
dlc = ir_datasets.util.DownloadConfig.context(NAME, base_path)
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
collection = FairTrecDocs(GzipExtract(dlc["docs"]), GzipExtract(dlc["metadata"]))
base = Dataset(
collection,
documentation('_'))
subsets = {}
train_topics = GzipExtract(dlc["train/topics"])
subsets['train'] = Dataset(
collection,
FairTrecQueries(train_topics, FairTrecQuery),
FairTrecQrels(train_topics),
documentation('train'))
subsets['eval'] = Dataset(
collection,
FairTrecQueries(GzipExtract(dlc['eval/topics']), FairTrecEvalQuery),
documentation('eval'))
ir_datasets.registry.register(NAME, base)
for s in subsets:
ir_datasets.registry.register(f'{NAME}/{s}', subsets[s])
return base, subsets
def _init():
subsets = {}
base_path = ir_datasets.util.home_path()/NAME
dlc = DownloadConfig.context(NAME, base_path)
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
collection = NytDocs(dlc['source'])
base = Dataset(collection, documentation('_'))
all_queries = NytQueries(collection)
all_qrels = NytQrels(collection)
match_qids = Lazy(lambda: VALID_IDS)
subsets['train'] = Dataset(
FilteredQueries(all_queries, match_qids, mode='exclude'),
FilteredQrels(all_qrels, match_qids, mode='exclude'),
collection,
documentation('train'))
subsets['valid'] = Dataset(
FilteredQueries(all_queries, match_qids, mode='include'),
FilteredQrels(all_qrels, match_qids, mode='include'),
collection,
documentation('valid'))
ir_datasets.registry.register('nyt', base)
for s in sorted(subsets):
ir_datasets.registry.register(f'nyt/{s}', subsets[s])
return base, subsets
def _init():
subsets = {}
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
base_path = ir_datasets.util.home_path()/NAME
dlc = DownloadConfig.context(NAME, base_path)
collection = TrecDocs(dlc['docs'], encoding='GB18030', path_globs=['**/xinhua/x*', '**/peoples-daily/pd*'], namespace=NAME, lang='zh', count_hint=ir_datasets.util.count_hint(NAME))
base = Dataset(collection, documentation('_'))
subsets['trec5'] = Dataset(
TrecQueries(GzipExtract(dlc['trec5/queries']), qtype=TrecMandarinQuery, qtype_map=QTYPE_MAP, encoding='GBK', namespace=NAME, lang=None), # queries have multiple languages
TrecQrels(GzipExtract(dlc['trec5/qrels']), QREL_DEFS),
collection,
documentation('trec5'))
subsets['trec6'] = Dataset(
TrecQueries(GzipExtract(dlc['trec6/queries']), qtype=TrecMandarinQuery, qtype_map=QTYPE_MAP, encoding='GBK', namespace=NAME, lang=None), # queries have multiple languages
TrecQrels(GzipExtract(dlc['trec6/qrels']), QREL_DEFS),
collection,
documentation('trec6'))
ir_datasets.registry.register(NAME, base)
for s in sorted(subsets):
ir_datasets.registry.register(f'{NAME}/{s}', subsets[s])
return base, subsets
def _init():
base_path = ir_datasets.util.home_path()/NAME
dlc = ir_datasets.util.DownloadConfig.context(NAME, base_path)
manager = NqManager(dlc, base_path)
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
collection = DocstoreBackedDocs(manager.docs_store, docs_cls=NqPassageDoc, namespace=NAME, lang='en')
base = Dataset(
collection,
documentation('_'))
subsets = {}
subsets['train'] = Dataset(
collection,
TsvQueries(manager.file_ref('train.queries.tsv'), namespace=NAME, lang='en'),
NqQrels(manager.file_ref('train.qrels.jsonl')),
NqScoredDocs(manager.file_ref('train.scoreddocs.tsv')),
documentation('train'),
)
subsets['dev'] = Dataset(
collection,
TsvQueries(manager.file_ref('dev.queries.tsv'), namespace=NAME, lang='en'),
NqQrels(manager.file_ref('dev.qrels.jsonl')),
NqScoredDocs(manager.file_ref('dev.scoreddocs.tsv')),
documentation('dev'),
)
ir_datasets.registry.register(NAME, base)
for s in sorted(subsets):
ir_datasets.registry.register(f'{NAME}/{s}', subsets[s])
return base, subsets
def _init():
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
base_path = ir_datasets.util.home_path() / NAME
dlc = DownloadConfig.context(NAME, base_path, dua=DUA)
subsets = {}
collection = TrecDocs(dlc['docs'],
path_globs=[
'**/FBIS/FB*', '**/FR94/??/FR*', '**/FT/*/FT*',
'**/LATIMES/LA*'
],
namespace=NAME,
lang='en',
expected_file_count=2295,
count_hint=ir_datasets.util.count_hint(NAME))
queries = TrecQueries(GzipExtract(dlc['queries']),
namespace=NAME,
lang='en')
qrels = TrecQrels(dlc['qrels'], QREL_DEFS)
base = Dataset(collection, queries, qrels, documentation('_'))
for fold in FOLDS:
qid_filter = make_filter(fold)
subsets[fold] = Dataset(FilteredQueries(queries, qid_filter),
FilteredQrels(qrels, qid_filter), collection,
documentation(fold))
ir_datasets.registry.register(NAME, base)
for s in sorted(subsets):
ir_datasets.registry.register(f'{NAME}/{s}', subsets[s])
return base, subsets
def _init():
subsets = {}
base_path = ir_datasets.util.home_path()/NAME
dlc = DownloadConfig.context(NAME, base_path)
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
base = Dataset(documentation('_')) # dummy top level ds
for lang in ['zh', 'fa', 'ru']:
lang_docs = HC4Docs(dlc[f'{lang}/docs'], subset_lang=lang)
subsets[lang] = Dataset(
lang_docs,
documentation(lang)
)
for sep in ['train', 'dev', 'test']:
subsets[f'{lang}/{sep}'] = Dataset(
lang_docs,
HC4Queries(dlc[f'{sep}/topics'], subset_lang=lang),
TrecQrels(dlc[f'{lang}/{sep}/qrels'], QREL_DEFS),
documentation(f'{lang}/{sep}'),
)
ir_datasets.registry.register(NAME, base)
for s in sorted(subsets):
ir_datasets.registry.register(f'{NAME}/{s}', subsets[s])
return base, subsets
def _init():
subsets = {}
base_path = ir_datasets.util.home_path() / NAME
dlc = DownloadConfig.context(NAME, base_path)
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
collection_v2 = WapoDocs(dlc['v2'])
base = Dataset(documentation('_'))
subsets['v2'] = Dataset(collection_v2, documentation('v2'))
subsets['v2/trec-core-2018'] = Dataset(
collection_v2,
TrecQueries(dlc['trec-core-2018/queries'],
namespace='trec-core-2018',
lang='en',
remove_tags=RM_TAGS),
TrecQrels(dlc['trec-core-2018/qrels'], CORE_QREL_DEFS),
documentation('v2/trec-core-2018'))
subsets['v2/trec-news-2018'] = Dataset(
collection_v2,
TrecQueries(dlc['trec-news-2018/queries'],
namespace='trec-news-2018',
lang='en',
qtype=TrecBackgroundLinkingQuery,
qtype_map=BL_MAP,
remove_tags=RM_TAGS),
TrecQrels(dlc['trec-news-2018/qrels'], BL_QREL_DEFS),
documentation('v2/trec-news-2018'))
subsets['v2/trec-news-2019'] = Dataset(
collection_v2,
TrecQueries(dlc['trec-news-2019/queries'],
namespace='trec-news-2019',
lang='en',
qtype=TrecBackgroundLinkingQuery,
qtype_map=BL_MAP,
remove_tags=RM_TAGS),
TrecQrels(dlc['trec-news-2019/qrels'], BL_QREL_DEFS),
documentation('v2/trec-news-2019'))
subsets['v3/trec-news-2020'] = Dataset(
TrecQueries(dlc['trec-news-2020/queries'],
namespace='trec-news-2020',
lang='en',
qtype=TrecBackgroundLinkingQuery,
qtype_map=BL_MAP,
remove_tags=RM_TAGS),
TrecQrels(dlc['trec-news-2020/qrels'], BL_QREL_DEFS),
documentation('v3/trec-news-2020'))
ir_datasets.registry.register(NAME, base)
for s in sorted(subsets):
ir_datasets.registry.register(f'{NAME}/{s}', subsets[s])
return base, subsets
def _init():
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
base_path = ir_datasets.util.home_path()/NAME
dlc = DownloadConfig.context(NAME, base_path)
subsets = {}
docs_dlc = dlc['docs']
docs_chk_dlc = TarExtractAll(dlc['docs.chk'], base_path/'corpus.chk')
b13_dlc = Bz2Extract(Cache(TarExtract(dlc['cw12b-info'], 'ClueWeb12-CreateB13/software/CreateClueWeb12B13Dataset.jar'), base_path/'CreateClueWeb12B13Dataset.jar'))
collection = ClueWeb12Docs(docs_dlc, docs_chk_dlc)
collection_b13 = ClueWeb12Docs(ClueWeb12b13Extractor(docs_dlc, b13_dlc))
base = Dataset(collection, documentation('_'))
subsets['b13'] = Dataset(collection_b13, documentation('b13'))
subsets['trec-web-2013'] = Dataset(
collection,
TrecXmlQueries(dlc['trec-web-2013/queries'], qtype=TrecWebTrackQuery, namespace=NAME),
TrecQrels(dlc['trec-web-2013/qrels.adhoc'], QREL_DEFS),
documentation('trec-web-2013'))
subsets['trec-web-2014'] = Dataset(
collection,
TrecXmlQueries(dlc['trec-web-2014/queries'], qtype=TrecWebTrackQuery, namespace=NAME),
TrecQrels(dlc['trec-web-2014/qrels.adhoc'], QREL_DEFS),
documentation('trec-web-2014'))
subsets['b13/ntcir-www-1'] = Dataset(
collection_b13,
TrecXmlQueries(Cache(ZipExtract(dlc['ntcir-www-1/queries'], 'eng.queries.xml'), base_path/'ntcir-www-1'/'queries.xml'), qtype=GenericQuery, qtype_map={'qid': 'query_id', 'content': 'text'}, namespace=NAME),
NtcirQrels(dlc['ntcir-www-1/qrels'], NTCIR_QREL_DEFS),
documentation('ntcir-www-1'))
subsets['b13/ntcir-www-2'] = Dataset(
collection_b13,
TrecXmlQueries(Cache(ZipExtract(dlc['ntcir-www-2/queries'], 'qEng.xml'), base_path/'ntcir-www-2'/'queries.xml'), qtype=NtcirQuery, qtype_map=ntcir_map, namespace=NAME),
NtcirQrels(dlc['ntcir-www-2/qrels'], NTCIR_QREL_DEFS),
documentation('ntcir-www-2'))
subsets['b13/ntcir-www-3'] = Dataset(
collection_b13,
TrecXmlQueries(dlc['ntcir-www-3/queries'], qtype=NtcirQuery, qtype_map=ntcir_map, namespace=NAME),
documentation('ntcir-www-3'))
subsets['b13/trec-misinfo-2019'] = Dataset(
collection_b13,
TrecXmlQueries(dlc['trec-misinfo-2019/queries'], qtype=MisinfoQuery, qtype_map=misinfo_map, namespace=NAME),
MsinfoQrels(dlc['trec-misinfo-2019/qrels'], MISINFO_QREL_DEFS),
documentation('trec-misinfo-2019'))
ir_datasets.registry.register(NAME, base)
for s in sorted(subsets):
ir_datasets.registry.register(f'{NAME}/{s}', subsets[s])
return base, subsets
def _init():
base_path = ir_datasets.util.home_path() / NAME
dlc = ir_datasets.util.DownloadConfig.context(NAME, base_path)
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
collection = TsvDocs(GzipExtract(dlc['docs']),
doc_cls=DprW100Doc,
namespace=NAME,
lang='en',
skip_first_line=True,
docstore_size_hint=12827215492,
count_hint=ir_datasets.util.count_hint(NAME))
base = Dataset(collection, documentation('_'))
subsets = {}
nq_dev_manager = DprW100Manager(GzipExtract(dlc['nq-dev']),
base_path / 'nq-dev')
subsets['natural-questions/dev'] = Dataset(
collection, DprW100Queries(nq_dev_manager.file_ref('queries.tsv')),
TrecQrels(nq_dev_manager.file_ref('qrels'), QREL_DEFS),
documentation('natural-questions/dev'))
nq_train_manager = DprW100Manager(GzipExtract(dlc['nq-train']),
base_path / 'nq-train')
subsets['natural-questions/train'] = Dataset(
collection, DprW100Queries(nq_train_manager.file_ref('queries.tsv')),
TrecQrels(nq_train_manager.file_ref('qrels'), QREL_DEFS),
documentation('natural-questions/train'))
tqa_dev_manager = DprW100Manager(GzipExtract(dlc['tqa-dev']),
base_path / 'tqa-dev',
passage_id_key='psg_id')
subsets['trivia-qa/dev'] = Dataset(
collection, DprW100Queries(tqa_dev_manager.file_ref('queries.tsv')),
TrecQrels(tqa_dev_manager.file_ref('qrels'), QREL_DEFS),
documentation('trivia-qa/dev'))
tqa_train_manager = DprW100Manager(GzipExtract(dlc['tqa-train']),
base_path / 'tqa-train',
passage_id_key='psg_id')
subsets['trivia-qa/train'] = Dataset(
collection, DprW100Queries(tqa_train_manager.file_ref('queries.tsv')),
TrecQrels(tqa_train_manager.file_ref('qrels'), QREL_DEFS),
documentation('trivia-qa/train'))
ir_datasets.registry.register(NAME, base)
for s in sorted(subsets):
ir_datasets.registry.register(f'{NAME}/{s}', subsets[s])
return base, subsets
def _init():
base_path = ir_datasets.util.home_path()/NAME
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
dlc = DownloadConfig.context(NAME, base_path, dua=DUA)
subsets = {}
migrator = Migrator(base_path/'irds_version.txt', 'v2',
affected_files=[base_path/'msmarco_v2_passage.tar.pklz4'],
message='Cleaning up pklz4 lookup structure in favor of ID-based lookups')
collection = MsMarcoV2Passages(dlc['passages'])
collection = migrator(collection)
qrels_migrator = Migrator(base_path/'qrels_version.txt', 'v2',
affected_files=[base_path/'train'/'qrels.tsv', base_path/'dev1'/'qrels.tsv', base_path/'dev2'/'qrels.tsv'],
message='Updating qrels (task organizers removed duplicates)')
subsets['train'] = Dataset(
collection,
TsvQueries(dlc['train/queries'], namespace='msmarco', lang='en'),
qrels_migrator(TrecQrels(dlc['train/qrels'], QRELS_DEFS)),
TrecScoredDocs(GzipExtract(dlc['train/scoreddocs'])),
)
subsets['dev1'] = Dataset(
collection,
TsvQueries(dlc['dev1/queries'], namespace='msmarco', lang='en'),
qrels_migrator(TrecQrels(dlc['dev1/qrels'], QRELS_DEFS)),
TrecScoredDocs(GzipExtract(dlc['dev1/scoreddocs'])),
)
subsets['dev2'] = Dataset(
collection,
TsvQueries(dlc['dev2/queries'], namespace='msmarco', lang='en'),
qrels_migrator(TrecQrels(dlc['dev2/qrels'], QRELS_DEFS)),
TrecScoredDocs(GzipExtract(dlc['dev2/scoreddocs'])),
)
subsets['trec-dl-2021'] = Dataset(
collection,
TsvQueries(dlc['trec-dl-2021/queries'], namespace='msmarco', lang='en'),
TrecQrels(dlc['trec-dl-2021/qrels'], TREC_DL_QRELS_DEFS),
TrecScoredDocs(GzipExtract(dlc['trec-dl-2021/scoreddocs'])),
)
dl21_judged = Lazy(lambda: {q.query_id for q in subsets['trec-dl-2021'].qrels_iter()})
subsets['trec-dl-2021/judged'] = Dataset(
FilteredQueries(subsets['trec-dl-2021'].queries_handler(), dl21_judged),
FilteredScoredDocs(subsets['trec-dl-2021'].scoreddocs_handler(), dl21_judged),
subsets['trec-dl-2021'],
)
ir_datasets.registry.register(NAME, Dataset(collection, documentation("_")))
for s in sorted(subsets):
ir_datasets.registry.register(f'{NAME}/{s}', Dataset(subsets[s], documentation(s)))
return collection, subsets
def _init():
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
base_path = ir_datasets.util.home_path()/NAME
dlc = DownloadConfig.context(NAME, base_path)
subsets = {}
base = Dataset(documentation('_'))
collection04 = MedlineDocs('2004', [GzipExtract(dlc['2004/a']), GzipExtract(dlc['2004/b']), GzipExtract(dlc['2004/c']), GzipExtract(dlc['2004/d'])], count_hint=ir_datasets.util.count_hint(f'{NAME}/2004'))
subsets['2004'] = Dataset(collection04, documentation('2004'))
subsets['2004/trec-genomics-2004'] = Dataset(
collection04,
TrecXmlQueries(ZipExtract(dlc['trec-genomics-2004/queries'], 'Official.xml'), qtype=TrecGenomicsQuery, qtype_map=TREC04_XML_MAP, namespace='trec-genomics', lang='en'),
TrecQrels(dlc['trec-genomics-2004/qrels'], QREL_DEFS),
documentation('trec-genomics-2004'),
)
subsets['2004/trec-genomics-2005'] = Dataset(
collection04,
TrecGenomicsQueries(dlc['trec-genomics-2005/queries']),
TrecQrels(dlc['trec-genomics-2005/qrels'], QREL_DEFS),
documentation('trec-genomics-2005'),
)
collection17 = ConcatDocs([
AacrAscoDocs(dlc['2017/aacr_asco_extra']),
MedlineDocs('2017', [dlc['2017/part1'], dlc['2017/part2'], dlc['2017/part3'], dlc['2017/part4'], dlc['2017/part5']]),
], count_hint=ir_datasets.util.count_hint(f'{NAME}/2017'))
subsets['2017'] = Dataset(collection17, documentation('2017'))
subsets['2017/trec-pm-2017'] = Dataset(
collection17,
TrecXmlQueries(dlc['trec-pm-2017/queries'], qtype=TrecPm2017Query, namespace='trec-pm-2017', lang='en'),
TrecQrels(dlc['trec-pm-2017/qrels'], QREL_DEFS),
documentation('trec-pm-2017'),
)
subsets['2017/trec-pm-2018'] = Dataset(
collection17,
TrecXmlQueries(dlc['trec-pm-2018/queries'], qtype=TrecPmQuery, namespace='trec-pm-2018', lang='en'),
TrecQrels(dlc['trec-pm-2018/qrels'], QREL_DEFS),
documentation('trec-pm-2018'),
)
ir_datasets.registry.register(NAME, base)
for s in sorted(subsets):
ir_datasets.registry.register(f'{NAME}/{s}', subsets[s])
return base, subsets
def _init():
base_path = home_path() / NAME
documentation = YamlDocumentation(f"docs/{NAME}.yaml")
download_config = DownloadConfig.context(NAME, base_path)
base = Dataset(documentation('_'))
# Arguments that can be loaded from Zenodo.
arguments: Dict[str, ArgsMeDocs] = {
name: ArgsMeDocs(Cache(ZipExtract(download_config[name], zip_path),
base_path / f"{name}.json"),
namespace=f"{NAME}/{name}",
language=language,
count_hint=count_hint)
for name, (count_hint, language, zip_path) in SUBSETS.items()
}
# Arguments that are combined versions of other subsets.
combined_arguments: Dict[str, ArgsMeCombinedArguments] = {
name: ArgsMeCombinedArguments(
base_path / f"{name}.json",
[arguments[subset_name] for subset_name in subset_names],
namespace=f"{NAME}/{name}",
language=language,
count_hint=count_hint)
for name, (subset_names, count_hint,
language) in COMBINED_SUBSETS.items()
}
# Wrap in datasets with documentation.
datasets = {
name: Dataset(arguments, documentation(name))
for name, arguments in chain(arguments.items(),
combined_arguments.items())
}
# NOTE: the following datasets are defined in touche.py:
# - argsme/1.0/touche-2020-task-1/uncorrected
# - argsme/2020-04-01/touche-2020-task-1
# - argsme/2020-04-01/touche-2020-task-1/uncorrected
# - argsme/2020-04-01/touche-2021-task-1
# Register datasets.
registry.register(NAME, base)
for name, arguments in datasets.items():
registry.register(f'{NAME}/{name}', arguments)
return base, datasets
def _init():
base_path = ir_datasets.util.home_path() / NAME
dlc = DownloadConfig.context(NAME, base_path)
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
subsets = {}
sources = [
('en1k', 'wikIR1k'),
('en59k', 'wikIR59k'),
('en78k', 'enwikIR'),
('ens78k', 'enwikIRS'),
('fr14k', 'FRwikIR14k'),
('es13k', 'ESwikIR13k'),
('it16k', 'ITwikIR16k'),
]
for source, zip_dir_name in sources:
source_dlc = ZipExtractCache(dlc[source], base_path / source)
docs = CsvDocs(
RelativePath(source_dlc, f"{zip_dir_name}/documents.csv"),
namespace=source,
lang=source[:2],
count_hint=ir_datasets.util.count_hint(f'{NAME}/{source}'),
docstore_path=ir_datasets.util.home_path() / NAME /
f'{source}.pklz4')
subsets[source] = Dataset(docs, documentation(source))
for split in ['training', 'validation', 'test']:
subsets[f'{source}/{split}'] = Dataset(
docs,
CsvQueries(RelativePath(source_dlc,
f"{zip_dir_name}/{split}/queries.csv"),
lang=source[:2]),
TrecQrels(RelativePath(source_dlc,
f"{zip_dir_name}/{split}/qrels"),
qrels_defs=QRELS_DEFS),
TrecScoredDocs(
RelativePath(source_dlc,
f"{zip_dir_name}/{split}/BM25.res")),
documentation(f'{source}/{split}'))
base = Dataset(documentation('_'))
ir_datasets.registry.register(NAME, base)
for s in sorted(subsets):
ir_datasets.registry.register(f'{NAME}/{s}', subsets[s])
return base, subsets
def _init():
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
base_path = ir_datasets.util.home_path() / NAME
dlc = DownloadConfig.context(NAME, base_path)
subsets = {}
langs = ['python', 'java', 'go', 'php', 'ruby', 'javascript']
dlcs = {
lang: ZipExtractCache(dlc[lang], base_path / lang)
for lang in langs
}
all_dlcs = [dlcs[lang] for lang in langs]
base = Dataset(
CodeSearchNetDocs(all_dlcs),
documentation('_'),
)
subsets['train'] = Dataset(
CodeSearchNetDocs(all_dlcs),
CodeSearchNetQueries(all_dlcs, 'train'),
CodeSearchNetQrels(all_dlcs, 'train'),
documentation('train'),
)
subsets['valid'] = Dataset(
CodeSearchNetDocs(all_dlcs),
CodeSearchNetQueries(all_dlcs, 'valid'),
CodeSearchNetQrels(all_dlcs, 'valid'),
documentation('valid'),
)
subsets['test'] = Dataset(
CodeSearchNetDocs(all_dlcs),
CodeSearchNetQueries(all_dlcs, 'test'),
CodeSearchNetQrels(all_dlcs, 'test'),
documentation('test'),
)
challenge_queries = CodeSearchNetChallengeQueries(dlc['challenge/queries'])
subsets['challenge'] = Dataset(
CodeSearchNetDocs(all_dlcs),
challenge_queries,
CodeSearchNetChallengeQrels(dlc['challenge/qrels'], challenge_queries),
documentation('challenge'),
)
ir_datasets.registry.register(NAME, base)
for s in sorted(subsets):
ir_datasets.registry.register(f'{NAME}/{s}', subsets[s])
return base, subsets
def _init():
subsets = {}
base_path = ir_datasets.util.home_path()/NAME
dlc = DownloadConfig.context(NAME, base_path)
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
migrator = Migrator(base_path/'irds_version.txt', 'v2',
affected_files=[base_path/'nyt.tgz.pklz4'],
message='Migrating nyt (extracting body text)')
collection = migrator(NytDocs(dlc['source']))
base = Dataset(collection, documentation('_'))
# core17
subsets['trec-core-2017'] = Dataset(
TrecQueries(dlc['trec-core-2017/queries'], namespace='trec-core-2017', lang='en'),
TrecQrels(dlc['trec-core-2017/qrels'], CORE_QREL_DEFS),
collection,
documentation('trec-core-2017'))
# wksup
all_queries = NytQueries(collection)
all_qrels = NytQrels(collection)
match_qids = Lazy(lambda: VALID_IDS)
subsets['wksup'] = Dataset(
all_queries,
all_qrels,
collection,
documentation('wksup/train'))
subsets['wksup/train'] = Dataset(
FilteredQueries(all_queries, match_qids, mode='exclude'),
FilteredQrels(all_qrels, match_qids, mode='exclude'),
collection,
documentation('wksup/train'))
subsets['wksup/valid'] = Dataset(
FilteredQueries(all_queries, match_qids, mode='include'),
FilteredQrels(all_qrels, match_qids, mode='include'),
collection,
documentation('wksup/valid'))
ir_datasets.registry.register('nyt', base)
for s in sorted(subsets):
ir_datasets.registry.register(f'nyt/{s}', subsets[s])
return base, subsets
def _init():
base_path = ir_datasets.util.home_path() / NAME
dlc = ir_datasets.util.DownloadConfig.context(NAME, base_path)
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
base_dlc = TarExtractAll(dlc['source'], base_path / 'lotte_extracted')
base = Dataset(documentation('_'))
subsets = {}
domains = [
('lifestyle', ),
('recreation', ),
('science', ),
('technology', ),
('writing', ),
('pooled', ),
]
for (domain, ) in domains:
for split in ['dev', 'test']:
corpus = TsvDocs(RelativePath(
base_dlc, f'lotte/{domain}/{split}/collection.tsv'),
lang='en')
subsets[f'{domain}/{split}'] = Dataset(
corpus, documentation(f'{domain}/{split}'))
for qtype in ['search', 'forum']:
subsets[f'{domain}/{split}/{qtype}'] = Dataset(
corpus,
TsvQueries(RelativePath(
base_dlc,
f'lotte/{domain}/{split}/questions.{qtype}.tsv'),
lang='en'),
LotteQrels(
RelativePath(
base_dlc,
f'lotte/{domain}/{split}/qas.{qtype}.jsonl')),
documentation(f'{domain}/{split}/{qtype}'))
ir_datasets.registry.register(NAME, base)
for s in sorted(subsets):
ir_datasets.registry.register(f'{NAME}/{s}', subsets[s])
return base, subsets
def _init():
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
base_path = ir_datasets.util.home_path()/NAME
dlc = DownloadConfig.context(NAME, base_path)
subsets = {}
collection = GovDocs(dlc['docs'])
base = Dataset(collection, documentation('_'))
subsets['trec-web-2002'] = Dataset(
collection,
TrecQueries(GzipExtract(dlc['trec-web-2002/queries']), namespace='gov/trec-web-2002', lang='en'),
TrecQrels(GzipExtract(dlc['trec-web-2002/qrels']), QREL_DEFS),
documentation('trec-web-2002')
)
subsets['trec-web-2002/named-page'] = Dataset(
collection,
TrecQueries(GzipExtract(dlc['trec-web-2002/named-page/queries']), qtype=GenericQuery, qtype_map=NAMED_PAGE_QTYPE_MAP, namespace='gov/trec-web-2002/named-page', lang='en'),
TrecQrels(GzipExtract(dlc['trec-web-2002/named-page/qrels']), NAMED_PAGE_QREL_DEFS),
documentation('trec-web-2002/named-page')
)
subsets['trec-web-2003'] = Dataset(
collection,
TrecQueries(dlc['trec-web-2003/queries'], qtype=GovWeb02Query, qtype_map=WEB03_QTYPE_MAP, namespace='gov/trec-web-2003', lang='en'),
TrecQrels(dlc['trec-web-2003/qrels'], QREL_DEFS),
documentation('trec-web-2003')
)
subsets['trec-web-2003/named-page'] = Dataset(
collection,
TrecQueries(dlc['trec-web-2003/named-page/queries'], qtype=GenericQuery, qtype_map=NAMED_PAGE_QTYPE_MAP, namespace='gov/trec-web-2003/named-page', lang='en'),
TrecQrels(dlc['trec-web-2003/named-page/qrels'], NAMED_PAGE_QREL_DEFS),
documentation('trec-web-2003/named-page')
)
subsets['trec-web-2004'] = Dataset(
collection,
TrecQueries(dlc['trec-web-2004/queries'], qtype=GenericQuery, qtype_map=WEB04_QTYPE_MAP, namespace='gov/trec-web-2004', lang='en'),
TrecQrels(dlc['trec-web-2004/qrels'], QREL_DEFS),
documentation('trec-web-2004')
)
ir_datasets.registry.register(NAME, base)
for s in sorted(subsets):
ir_datasets.registry.register(f'{NAME}/{s}', subsets[s])
return base, subsets
def _init():
base_path = ir_datasets.util.home_path()/NAME
dlc = DownloadConfig.context(NAME, base_path, dua=DUA)
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
manager = MsMarcoQnAManager(GzipExtract(dlc['train']), GzipExtract(dlc['dev']), GzipExtract(dlc['eval']), base_path)
migrator = Migrator(base_path/'irds_version.txt', 'v2',
affected_files=[
base_path/'docs.pklz4',
base_path/'train.run', base_path/'train.qrels',
base_path/'dev.run', base_path/'dev.qrels',
base_path/'eval.run',
],
message='Migrating msmarco-qna (correcting doc_ids)')
collection = DocstoreBackedDocs(manager.docs_store, docs_cls=MsMarcoQnADoc, namespace=NAME, lang='en')
collection = migrator(collection)
subsets = {}
subsets['train'] = Dataset(
collection,
TsvQueries(manager.file_ref('train.queries.tsv'), query_cls=MsMarcoQnAQuery, namespace='msmarco', lang='en'),
migrator(TrecQrels(manager.file_ref('train.qrels'), QRELS_DEFS)),
migrator(TrecScoredDocs(manager.file_ref('train.run'))),
)
subsets['dev'] = Dataset(
collection,
TsvQueries(manager.file_ref('dev.queries.tsv'), query_cls=MsMarcoQnAQuery, namespace='msmarco', lang='en'),
migrator(TrecQrels(manager.file_ref('dev.qrels'), QRELS_DEFS)),
migrator(TrecScoredDocs(manager.file_ref('dev.run'))),
)
subsets['eval'] = Dataset(
collection,
TsvQueries(manager.file_ref('eval.queries.tsv'), query_cls=MsMarcoQnAEvalQuery, namespace='msmarco', lang='en'),
migrator(TrecScoredDocs(manager.file_ref('eval.run'))),
)
ir_datasets.registry.register(NAME, Dataset(collection, documentation('_')))
for s in sorted(subsets):
ir_datasets.registry.register(f'{NAME}/{s}', Dataset(subsets[s], documentation(s)))
return collection, subsets
def _init():
subsets = {}
base_path = ir_datasets.util.home_path() / NAME
dlc = DownloadConfig.context(NAME, base_path)
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
collection = TrecDocs(
dlc['docs'],
encoding='ISO-8859-1',
path_globs=['**/afp_text/af*', '**/infosel_data/ism_*'],
namespace=NAME,
lang='es',
count_hint=ir_datasets.util.count_hint(NAME))
base = Dataset(collection, documentation('_'))
subsets['trec3'] = Dataset(
TrecSpanishTranslateQueries(
TrecQueries(GzipExtract(dlc['trec3/queries']),
qtype_map=QTYPE_MAP_3,
encoding='ISO-8859-1',
namespace=NAME,
lang=None), TrecSpanish3Query),
TrecQrels(GzipExtract(dlc['trec3/qrels']), QREL_DEFS), collection,
documentation('trec3'))
subsets['trec4'] = Dataset(
TrecSpanishTranslateQueries(
TrecQueries(GzipExtract(dlc['trec4/queries']),
qtype=TrecDescOnlyQuery,
qtype_map=QTYPE_MAP_4,
encoding='ISO-8859-1',
namespace=NAME,
lang=None), TrecSpanish4Query),
TrecQrels(GzipExtract(dlc['trec4/qrels']), QREL_DEFS), collection,
documentation('trec4'))
ir_datasets.registry.register(NAME, base)
for s in sorted(subsets):
ir_datasets.registry.register(f'{NAME}/{s}', subsets[s])
return base, subsets
def _init():
subsets = {}
base_path = ir_datasets.util.home_path()/NAME
dlc = DownloadConfig.context(NAME, base_path)
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
collection = Cord19Docs(dlc['docs/2020-07-16'], base_path/'2020-07-16', '2020-07-16')
base = Dataset(collection, documentation('_'))
subsets['trec-covid'] = Dataset(
TrecXmlQueries(dlc['trec-covid/queries'], qtype_map={'query': 'title', 'question': 'description', 'narrative': 'narrative'}, namespace=NAME),
TrecQrels(dlc['trec-covid/qrels'], QRELS_DEFS),
collection,
documentation('trec-covid'))
ir_datasets.registry.register(NAME, base)
for s in sorted(subsets):
ir_datasets.registry.register(f'{NAME}/{s}', subsets[s])
return base, subsets
def _init():
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
base_path = ir_datasets.util.home_path() / NAME
dlc = DownloadConfig.context(NAME, base_path)
subsets = {}
main_dlc = dlc['main']
base = Dataset(
VaswaniDocs(
Cache(TarExtract(main_dlc, 'doc-text'), base_path / 'docs.txt')),
VaswaniQueries(
Cache(TarExtract(main_dlc, 'query-text'),
base_path / 'queries.txt')),
VaswaniQrels(
Cache(TarExtract(main_dlc, 'rlv-ass'), base_path / 'qrels.txt')),
documentation('_'),
)
ir_datasets.registry.register(NAME, base)
for s in sorted(subsets):
ir_datasets.registry.register(f'{NAME}/{s}', subsets[s])
return base, subsets
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))
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
def _init():
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
base_path = ir_datasets.util.home_path() / NAME
dlc = DownloadConfig.context(NAME, base_path)
subsets = {}
collection = MedlineDocs([
GzipExtract(dlc['docs/a']),
GzipExtract(dlc['docs/b']),
GzipExtract(dlc['docs/c']),
GzipExtract(dlc['docs/d'])
])
base = Dataset(collection, documentation('_'))
subsets['trec-genomics-2004'] = Dataset(
collection,
TrecXmlQueries(ZipExtract(dlc['trec-genomics-2004/queries'],
'Official.xml'),
qtype=TrecGenomicsQuery,
qtype_map=TREC04_XML_MAP,
namespace='trec-genomics'),
TrecQrels(dlc['trec-genomics-2004/qrels'], QREL_DEFS),
documentation('trec-genomics-2004'),
)
subsets['trec-genomics-2005'] = Dataset(
collection,
TrecGenomicsQueries(dlc['trec-genomics-2005/queries']),
TrecQrels(dlc['trec-genomics-2005/qrels'], QREL_DEFS),
documentation('trec-genomics-2005'),
)
ir_datasets.registry.register(NAME, base)
for s in sorted(subsets):
ir_datasets.registry.register(f'{NAME}/{s}', subsets[s])
return base, subsets
def _init():
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
base_path = ir_datasets.util.home_path() / NAME
dlc = DownloadConfig.context(NAME, base_path)
subsets = {}
main_dlc = dlc['main']
base = Dataset(
CranfieldDocs(
Cache(TarExtract(main_dlc, 'cran.all.1400'),
base_path / 'docs.txt')),
CranfieldQueries(
Cache(TarExtract(main_dlc, 'cran.qry'),
base_path / 'queries.txt')),
CranfieldQrels(
Cache(TarExtract(main_dlc, 'cranqrel'), base_path / 'qrels.txt')),
documentation('_'),
)
ir_datasets.registry.register(NAME, base)
for s in sorted(subsets):
ir_datasets.registry.register(f'{NAME}/{s}', subsets[s])
return base, subsets
def _init():
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
base_path = ir_datasets.util.home_path() / NAME
dlc = DownloadConfig.context(NAME, base_path, dua=DUA)
migrator = Migrator(base_path / 'irds_version.txt',
'v2',
affected_files=[
base_path / 'collection.tsv',
base_path / 'collection.tsv.pklz4'
],
message=f'Migrating {NAME} (fixing passage encoding)')
collection = TsvDocs(Cache(
FixEncoding(TarExtract(dlc['collectionandqueries'], 'collection.tsv')),
base_path / 'collection.tsv'),
namespace='msmarco',
lang='en',
docstore_size_hint=14373971970,
count_hint=ir_datasets.util.count_hint(NAME))
collection = migrator(collection)
subsets = {}
subsets['train'] = Dataset(
collection,
TsvQueries(Cache(TarExtract(dlc['queries'], 'queries.train.tsv'),
base_path / 'train/queries.tsv'),
namespace='msmarco',
lang='en'),
TrecQrels(dlc['train/qrels'], QRELS_DEFS),
TsvDocPairs(GzipExtract(dlc['train/docpairs'])),
TrecScoredDocs(
Cache(
ExtractQidPid(
TarExtract(dlc['train/scoreddocs'], 'top1000.train.txt')),
base_path / 'train/ms.run')),
)
subsets['train/triples-v2'] = Dataset(
collection,
subsets['train'].queries_handler(),
subsets['train'].qrels_handler(),
TsvDocPairs(GzipExtract(dlc['train/docpairs/v2'])),
subsets['train'].scoreddocs_handler(),
)
subsets['train/triples-small'] = Dataset(
collection,
subsets['train'].queries_handler(),
subsets['train'].qrels_handler(),
TsvDocPairs(
Cache(
MapSmallTriplesQidPid(
TarExtract(dlc['train/docpairs/small'],
'triples.train.small.tsv'),
TarExtract(dlc['collectionandqueries'], 'collection.tsv'),
subsets['train'].queries_handler()),
base_path / 'train/small.triples.qidpid.tsv')),
subsets['train'].scoreddocs_handler(),
)
subsets['dev'] = Dataset(
collection,
TsvQueries(Cache(TarExtract(dlc['queries'], 'queries.dev.tsv'),
base_path / 'dev/queries.tsv'),
namespace='msmarco',
lang='en'),
TrecQrels(dlc['dev/qrels'], QRELS_DEFS),
)
subsets['dev/small'] = Dataset(
collection,
TsvQueries(Cache(
TarExtract(dlc['collectionandqueries'], 'queries.dev.small.tsv'),
base_path / 'dev/small/queries.tsv'),
namespace='msmarco',
lang='en'),
TrecQrels(
Cache(
TarExtract(dlc['collectionandqueries'], 'qrels.dev.small.tsv'),
base_path / 'dev/small/qrels'), QRELS_DEFS),
TrecScoredDocs(
Cache(
ExtractQidPid(TarExtract(dlc['dev/scoreddocs'],
'top1000.dev')),
base_path / 'dev/ms.run')),
)
subsets['eval'] = Dataset(
collection,
TsvQueries(Cache(TarExtract(dlc['queries'], 'queries.eval.tsv'),
base_path / 'eval/queries.tsv'),
namespace='msmarco',
lang='en'),
)
subsets['eval/small'] = Dataset(
collection,
TsvQueries(Cache(
TarExtract(dlc['collectionandqueries'], 'queries.eval.small.tsv'),
base_path / 'eval/small/queries.tsv'),
namespace='msmarco',
lang='en'),
TrecScoredDocs(
Cache(
ExtractQidPid(
TarExtract(dlc['eval/scoreddocs'], 'top1000.eval')),
base_path / 'eval/ms.run')),
)
subsets['trec-dl-2019'] = Dataset(
collection,
TrecQrels(dlc['trec-dl-2019/qrels'], TREC_DL_QRELS_DEFS),
TsvQueries(Cache(GzipExtract(dlc['trec-dl-2019/queries']),
base_path / 'trec-dl-2019/queries.tsv'),
namespace='msmarco',
lang='en'),
TrecScoredDocs(
Cache(ExtractQidPid(GzipExtract(dlc['trec-dl-2019/scoreddocs'])),
base_path / 'trec-dl-2019/ms.run')),
)
subsets['trec-dl-2020'] = Dataset(
collection,
TsvQueries(GzipExtract(dlc['trec-dl-2020/queries']),
namespace='msmarco',
lang='en'),
TrecQrels(dlc['trec-dl-2020/qrels'], TREC_DL_QRELS_DEFS),
TrecScoredDocs(
Cache(ExtractQidPid(GzipExtract(dlc['trec-dl-2020/scoreddocs'])),
base_path / 'trec-dl-2020/ms.run')),
)
# A few subsets that are contrainted to just the queries/qrels/docpairs that have at least
# 1 relevance assessment
train_judged = Lazy(
lambda: {q.query_id
for q in subsets['train'].qrels_iter()})
subsets['train/judged'] = Dataset(
FilteredQueries(subsets['train'].queries_handler(), train_judged),
FilteredScoredDocs(subsets['train'].scoreddocs_handler(),
train_judged),
subsets['train'],
)
dev_judged = Lazy(
lambda: {q.query_id
for q in subsets['dev'].qrels_iter()})
subsets['dev/judged'] = Dataset(
FilteredQueries(subsets['dev'].queries_handler(), dev_judged),
subsets['dev'],
)
dl19_judged = Lazy(
lambda: {q.query_id
for q in subsets['trec-dl-2019'].qrels_iter()})
subsets['trec-dl-2019/judged'] = Dataset(
FilteredQueries(subsets['trec-dl-2019'].queries_handler(),
dl19_judged),
FilteredScoredDocs(subsets['trec-dl-2019'].scoreddocs_handler(),
dl19_judged),
subsets['trec-dl-2019'],
)
dl20_judged = Lazy(
lambda: {q.query_id
for q in subsets['trec-dl-2020'].qrels_iter()})
subsets['trec-dl-2020/judged'] = Dataset(
FilteredQueries(subsets['trec-dl-2020'].queries_handler(),
dl20_judged),
FilteredScoredDocs(subsets['trec-dl-2020'].scoreddocs_handler(),
dl20_judged),
subsets['trec-dl-2020'],
)
# split200 -- 200 queries held out from the training data for validation
split200 = Lazy(lambda: SPLIT200_QIDS)
subsets['train/split200-train'] = Dataset(
FilteredQueries(subsets['train'].queries_handler(),
split200,
mode='exclude'),
FilteredScoredDocs(subsets['train'].scoreddocs_handler(),
split200,
mode='exclude'),
FilteredQrels(subsets['train'].qrels_handler(),
split200,
mode='exclude'),
FilteredDocPairs(subsets['train'].docpairs_handler(),
split200,
mode='exclude'),
subsets['train'],
)
subsets['train/split200-valid'] = Dataset(
FilteredQueries(subsets['train'].queries_handler(),
split200,
mode='include'),
FilteredScoredDocs(subsets['train'].scoreddocs_handler(),
split200,
mode='include'),
FilteredQrels(subsets['train'].qrels_handler(),
split200,
mode='include'),
FilteredDocPairs(subsets['train'].docpairs_handler(),
split200,
mode='include'),
subsets['train'],
)
# Medical subset
def train_med():
with dlc['medmarco_ids'].stream() as stream:
stream = codecs.getreader('utf8')(stream)
return {l.rstrip() for l in stream}
train_med = Lazy(train_med)
subsets['train/medical'] = Dataset(
FilteredQueries(subsets['train'].queries_handler(), train_med),
FilteredScoredDocs(subsets['train'].scoreddocs_handler(), train_med),
FilteredDocPairs(subsets['train'].docpairs_handler(), train_med),
FilteredQrels(subsets['train'].qrels_handler(), train_med),
subsets['train'],
)
# DL-Hard
dl_hard_qrels_migrator = Migrator(
base_path / 'trec-dl-hard' / 'irds_version.txt',
'v3',
affected_files=[base_path / 'trec-dl-hard' / 'qrels'],
message='Updating trec-dl-hard qrels')
hard_qids = Lazy(lambda: DL_HARD_QIDS)
dl_hard_base_queries = TsvQueries([
Cache(GzipExtract(dlc['trec-dl-2019/queries']),
base_path / 'trec-dl-2019/queries.tsv'),
Cache(GzipExtract(dlc['trec-dl-2020/queries']),
base_path / 'trec-dl-2020/queries.tsv')
],
namespace='msmarco',
lang='en')
subsets['trec-dl-hard'] = Dataset(
collection, FilteredQueries(dl_hard_base_queries, hard_qids),
dl_hard_qrels_migrator(
TrecQrels(dlc['trec-dl-hard/qrels'], TREC_DL_QRELS_DEFS)),
documentation('trec-dl-hard'))
hard_qids = Lazy(lambda: DL_HARD_QIDS_BYFOLD['1'])
subsets['trec-dl-hard/fold1'] = Dataset(
collection, FilteredQueries(dl_hard_base_queries, hard_qids),
FilteredQrels(subsets['trec-dl-hard'], hard_qids),
documentation('trec-dl-hard/fold1'))
hard_qids = Lazy(lambda: DL_HARD_QIDS_BYFOLD['2'])
subsets['trec-dl-hard/fold2'] = Dataset(
collection, FilteredQueries(dl_hard_base_queries, hard_qids),
FilteredQrels(subsets['trec-dl-hard'], hard_qids),
documentation('trec-dl-hard/fold2'))
hard_qids = Lazy(lambda: DL_HARD_QIDS_BYFOLD['3'])
subsets['trec-dl-hard/fold3'] = Dataset(
collection, FilteredQueries(dl_hard_base_queries, hard_qids),
FilteredQrels(subsets['trec-dl-hard'], hard_qids),
documentation('trec-dl-hard/fold3'))
hard_qids = Lazy(lambda: DL_HARD_QIDS_BYFOLD['4'])
subsets['trec-dl-hard/fold4'] = Dataset(
collection, FilteredQueries(dl_hard_base_queries, hard_qids),
FilteredQrels(subsets['trec-dl-hard'], hard_qids),
documentation('trec-dl-hard/fold4'))
hard_qids = Lazy(lambda: DL_HARD_QIDS_BYFOLD['5'])
subsets['trec-dl-hard/fold5'] = Dataset(
collection, FilteredQueries(dl_hard_base_queries, hard_qids),
FilteredQrels(subsets['trec-dl-hard'], hard_qids),
documentation('trec-dl-hard/fold5'))
ir_datasets.registry.register(NAME, Dataset(collection,
documentation('_')))
for s in sorted(subsets):
ir_datasets.registry.register(f'{NAME}/{s}',
Dataset(subsets[s], documentation(s)))
return collection, subsets
def _init():
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
base_path = ir_datasets.util.home_path() / NAME
dlc = DownloadConfig.context(NAME, base_path)
subsets = {}
docs_dlc = dlc['docs']
docs_chk_dlc = TarExtractAll(dlc['docs.chk'], base_path / 'corpus.chk')
b13_dlc = Bz2Extract(
Cache(
TarExtract(
dlc['cw12b-info'],
'ClueWeb12-CreateB13/software/CreateClueWeb12B13Dataset.jar'),
base_path / 'CreateClueWeb12B13Dataset.jar'))
collection = ClueWeb12Docs(docs_dlc, docs_chk_dlc)
collection_b13 = ClueWeb12Docs(ClueWeb12b13Extractor(docs_dlc, b13_dlc))
base = Dataset(collection, documentation('_'))
subsets['b13'] = Dataset(collection_b13, documentation('b13'))
subsets['trec-web-2013'] = Dataset(
collection,
TrecXmlQueries(dlc['trec-web-2013/queries'],
qtype=TrecWebTrackQuery,
namespace='trec-web',
lang='en'),
TrecQrels(dlc['trec-web-2013/qrels.adhoc'], QREL_DEFS),
documentation('trec-web-2013'))
subsets['trec-web-2014'] = Dataset(
collection,
TrecXmlQueries(dlc['trec-web-2014/queries'],
qtype=TrecWebTrackQuery,
namespace='trec-web',
lang='en'),
TrecQrels(dlc['trec-web-2014/qrels.adhoc'], QREL_DEFS),
documentation('trec-web-2014'))
subsets['b13/ntcir-www-1'] = Dataset(
collection_b13,
TrecXmlQueries(Cache(
ZipExtract(dlc['ntcir-www-1/queries'], 'eng.queries.xml'),
base_path / 'ntcir-www-1' / 'queries.xml'),
qtype=GenericQuery,
qtype_map={
'qid': 'query_id',
'content': 'text'
},
namespace='ntcir-www',
lang='en'),
NtcirQrels(dlc['ntcir-www-1/qrels'], NTCIR_QREL_DEFS),
documentation('ntcir-www-1'))
subsets['b13/ntcir-www-2'] = Dataset(
collection_b13,
TrecXmlQueries(Cache(
ZipExtract(dlc['ntcir-www-2/queries'], 'qEng.xml'),
base_path / 'ntcir-www-2' / 'queries.xml'),
qtype=NtcirQuery,
qtype_map=ntcir_map,
namespace='ntcir-www',
lang='en'),
NtcirQrels(dlc['ntcir-www-2/qrels'], NTCIR_QREL_DEFS),
documentation('ntcir-www-2'))
subsets['b13/ntcir-www-3'] = Dataset(
collection_b13,
TrecXmlQueries(dlc['ntcir-www-3/queries'],
qtype=NtcirQuery,
qtype_map=ntcir_map,
namespace='ntcir-www',
lang='en'), documentation('ntcir-www-3'))
subsets['b13/trec-misinfo-2019'] = Dataset(
collection_b13,
TrecXmlQueries(dlc['trec-misinfo-2019/queries'],
qtype=MisinfoQuery,
qtype_map=misinfo_map,
namespace='trec-misinfo-2019',
lang='en'),
MsinfoQrels(dlc['trec-misinfo-2019/qrels'], MISINFO_QREL_DEFS),
documentation('trec-misinfo-2019'))
subsets['b13/clef-ehealth'] = Dataset(
collection_b13,
TrecXmlQueries(FixAmp(dlc['clef-ehealth/queries']),
qtype=GenericQuery,
qtype_map=ehealth_map,
namespace='clef-ehealth',
lang='en'),
EhealthQrels(
[dlc['clef-ehealth/2016.qrels'], dlc['clef-ehealth/2017.qrels']],
[dlc['clef-ehealth/2016.qtrust'], dlc['clef-ehealth/2017.qtrust']],
[dlc['clef-ehealth/2016.qunder'], dlc['clef-ehealth/2017.qreads']],
EHEALTH_QREL_DEFS), documentation('clef-ehealth'))
subsets['b13/clef-ehealth/cs'] = Dataset(
collection_b13,
TrecXmlQueries(FixAmp(dlc['clef-ehealth/queries/cs']),
qtype=GenericQuery,
qtype_map=ehealth_map,
namespace='clef-ehealth',
lang='cs'),
EhealthQrels(
[dlc['clef-ehealth/2016.qrels'], dlc['clef-ehealth/2017.qrels']],
[dlc['clef-ehealth/2016.qtrust'], dlc['clef-ehealth/2017.qtrust']],
[dlc['clef-ehealth/2016.qunder'], dlc['clef-ehealth/2017.qreads']],
EHEALTH_QREL_DEFS,
query_id_suffix='-cs'), documentation('clef-ehealth/cs'))
subsets['b13/clef-ehealth/de'] = Dataset(
collection_b13,
TrecXmlQueries(FixAmp(dlc['clef-ehealth/queries/de']),
qtype=GenericQuery,
qtype_map=ehealth_map,
namespace='clef-ehealth',
lang='de'),
EhealthQrels(
[dlc['clef-ehealth/2016.qrels'], dlc['clef-ehealth/2017.qrels']],
[dlc['clef-ehealth/2016.qtrust'], dlc['clef-ehealth/2017.qtrust']],
[dlc['clef-ehealth/2016.qunder'], dlc['clef-ehealth/2017.qreads']],
EHEALTH_QREL_DEFS,
query_id_suffix='-de'), documentation('clef-ehealth/de'))
subsets['b13/clef-ehealth/fr'] = Dataset(
collection_b13,
TrecXmlQueries(FixAmp(dlc['clef-ehealth/queries/fr']),
qtype=GenericQuery,
qtype_map=ehealth_map,
namespace='clef-ehealth',
lang='fr'),
EhealthQrels(
[dlc['clef-ehealth/2016.qrels'], dlc['clef-ehealth/2017.qrels']],
[dlc['clef-ehealth/2016.qtrust'], dlc['clef-ehealth/2017.qtrust']],
[dlc['clef-ehealth/2016.qunder'], dlc['clef-ehealth/2017.qreads']],
EHEALTH_QREL_DEFS,
query_id_suffix='-fr'), documentation('clef-ehealth/fr'))
subsets['b13/clef-ehealth/hu'] = Dataset(
collection_b13,
TrecXmlQueries(FixAmp(dlc['clef-ehealth/queries/hu']),
qtype=GenericQuery,
qtype_map=ehealth_map,
namespace='clef-ehealth',
lang='hu'),
EhealthQrels(
[dlc['clef-ehealth/2016.qrels'], dlc['clef-ehealth/2017.qrels']],
[dlc['clef-ehealth/2016.qtrust'], dlc['clef-ehealth/2017.qtrust']],
[dlc['clef-ehealth/2016.qunder'], dlc['clef-ehealth/2017.qreads']],
EHEALTH_QREL_DEFS,
query_id_suffix='-hu'), documentation('clef-ehealth/hu'))
subsets['b13/clef-ehealth/pl'] = Dataset(
collection_b13,
TrecXmlQueries(FixAmp(dlc['clef-ehealth/queries/pl']),
qtype=GenericQuery,
qtype_map=ehealth_map,
namespace='clef-ehealth',
lang='pl'),
EhealthQrels(
[dlc['clef-ehealth/2016.qrels'], dlc['clef-ehealth/2017.qrels']],
[dlc['clef-ehealth/2016.qtrust'], dlc['clef-ehealth/2017.qtrust']],
[dlc['clef-ehealth/2016.qunder'], dlc['clef-ehealth/2017.qreads']],
EHEALTH_QREL_DEFS,
query_id_suffix='-pl'), documentation('clef-ehealth/pl'))
subsets['b13/clef-ehealth/sv'] = Dataset(
collection_b13,
TrecXmlQueries(FixAmp(dlc['clef-ehealth/queries/sv']),
qtype=GenericQuery,
qtype_map=ehealth_map,
namespace='clef-ehealth',
lang='sv'),
EhealthQrels(
[dlc['clef-ehealth/2016.qrels'], dlc['clef-ehealth/2017.qrels']],
[dlc['clef-ehealth/2016.qtrust'], dlc['clef-ehealth/2017.qtrust']],
[dlc['clef-ehealth/2016.qunder'], dlc['clef-ehealth/2017.qreads']],
EHEALTH_QREL_DEFS,
query_id_suffix='-sv'), documentation('clef-ehealth/sv'))
# NOTE: the following datasets are defined in touche.py:
# - clueweb12/touche-2020-task-2
# - clueweb12/touche-2021-task-2
ir_datasets.registry.register(NAME, base)
for s in sorted(subsets):
ir_datasets.registry.register(f'{NAME}/{s}', subsets[s])
return base, subsets