Datasets:
Tasks:
Text Retrieval
Sub-tasks:
document-retrieval
Size Categories:
100K<n<1M
Annotations Creators:
no-annotation
Source Datasets:
extended|csl
Tags:
License:
File size: 1,563 Bytes
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import gzip
import json
import datasets
_URLS = {
"csl": "https://huggingface.co/datasets/neuclir/csl/resolve/main/data/csl.jsonl.gz",
"en_translation": "https://huggingface.co/datasets/neuclir/csl/resolve/main/data/csl.gt.063023.jsonl.gz",
}
class Csl(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("1.1.1")
def _info(self):
return datasets.DatasetInfo(
features=datasets.Features({
"doc_id": datasets.Value("string"),
"title": datasets.Value("string"),
"abstract": datasets.Value("string"),
"keywords": datasets.Sequence(feature=datasets.Value("string"), length=-1),
"category": datasets.Value("string"),
"category_eng": datasets.Value("string"),
"discipline": datasets.Value("string"),
"discipline_eng": datasets.Value("string"),
}),
)
def _split_generators(self, dl_manager):
paths = dl_manager.download(_URLS)
return [
datasets.SplitGenerator(
name=split,
gen_kwargs={
"filepath": paths[split],
})
for split in _URLS
]
def _generate_examples(self, filepath):
with gzip.open(filepath) as f:
for key, row in enumerate(f):
data = json.loads(row)
if "category_eng" not in data:
data["category_eng"] = ""
data["discipline_eng"] = ""
yield key, data
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