Datasets:
Languages:
English
Multilinguality:
monolingual
Size Categories:
unknown
Language Creators:
machine-generated
Annotations Creators:
expert-generated
Source Datasets:
original
License:
| """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 = """ | |
| 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() | |
| } |