Datasets:
Tasks:
Token Classification
Modalities:
Text
Sub-tasks:
coreference-resolution
Languages:
English
Size:
< 1K
License:
File size: 1,782 Bytes
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"""SciCo"""
import os
import jsonlines
import datasets
_CITATION = """\
@inproceedings{
cattan2021scico,
title={SciCo: Hierarchical Cross-Document Coreference for Scientific Concepts},
author={Arie Cattan and Sophie Johnson and Daniel S. Weld and Ido Dagan and Iz Beltagy and Doug Downey and Tom Hope},
booktitle={3rd Conference on Automated Knowledge Base Construction},
year={2021},
url={https://openreview.net/forum?id=OFLbgUP04nC}
}
"""
_DESCRIPTION = """\
SciCo is a dataset for hierarchical cross-document coreference resolution
over scientific papers in the CS domain.
"""
_DATA_URL = https://nlp.biu.ac.il/~ariecattan/scico/data.tar
class Scico(datasets.GeneratorBasedBuilder):
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
homepage="https://scico.apps.allenai.org/",
citation = _CITATION)
def _split_generators(self, dl_manager):
data_dir = dl_manager.download_and_extract(_DATA_URL)
return [
datasets.SplitGenerator(
name=datasets.Split.TEST, gen_kwargs={"filepath": os.path.join(data_dir, "test.jsonl")}
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION, gen_kwargs={"filepath": os.path.join(data_dir, "dev.jsonl")}
),
datasets.SplitGenerator(
name=datasets.Split.TRAIN, gen_kwargs={"filepath": os.path.join(data_dir, "train.jsonl")}
),
]
def _generate_examples(self, filepath):
"""This function returns the examples in the raw (text) form."""
with jsonlines.open(filepath, 'r') as f:
for topic in f:
yield topic
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