| | """SNAP dataset"""
|
| |
|
| | import datasets
|
| |
|
| | _CITATION = """
|
| | @inproceedings{celebi2016segmenting,
|
| | title={Segmenting hashtags using automatically created training data},
|
| | author={Celebi, Arda and {\"O}zg{\"u}r, Arzucan},
|
| | booktitle={Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)},
|
| | pages={2981--2985},
|
| | year={2016}
|
| | }
|
| | """
|
| |
|
| | _DESCRIPTION = """
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| | Automatically segmented 803K SNAP Twitter Data Set hashtags with the heuristic described in the paper "Segmenting hashtags using automatically created training data".
|
| | """
|
| | _URL = "https://raw.githubusercontent.com/ruanchaves/hashformers/master/datasets/SNAP.Hashtags.Segmented.w.Heuristics.txt"
|
| |
|
| | class Snap(datasets.GeneratorBasedBuilder):
|
| |
|
| | VERSION = datasets.Version("1.0.0")
|
| |
|
| | def _info(self):
|
| | return datasets.DatasetInfo(
|
| | description=_DESCRIPTION,
|
| | features=datasets.Features(
|
| | {
|
| | "index": datasets.Value("int32"),
|
| | "hashtag": datasets.Value("string"),
|
| | "segmentation": datasets.Value("string")
|
| | }
|
| | ),
|
| | supervised_keys=None,
|
| | homepage="https://github.com/ardax/hashtag-segmentor",
|
| | citation=_CITATION,
|
| | )
|
| |
|
| | def _split_generators(self, dl_manager):
|
| | downloaded_files = dl_manager.download(_URL)
|
| | return [
|
| | datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files}),
|
| | ]
|
| |
|
| | def _generate_examples(self, filepath):
|
| |
|
| | with open(filepath, 'r') as f:
|
| | for idx, line in enumerate(f):
|
| | yield idx, {
|
| | "index": idx,
|
| | "hashtag": line.strip().replace(" ", ""),
|
| | "segmentation": line.strip()
|
| | } |
