Datasets:
Commit
·
d421e49
1
Parent(s):
8d3e782
Upload snap.py
Browse files
snap.py
ADDED
|
@@ -0,0 +1,53 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
"""SNAP dataset"""
|
| 2 |
+
|
| 3 |
+
import datasets
|
| 4 |
+
|
| 5 |
+
_CITATION = """
|
| 6 |
+
@inproceedings{celebi2016segmenting,
|
| 7 |
+
title={Segmenting hashtags using automatically created training data},
|
| 8 |
+
author={Celebi, Arda and {\"O}zg{\"u}r, Arzucan},
|
| 9 |
+
booktitle={Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)},
|
| 10 |
+
pages={2981--2985},
|
| 11 |
+
year={2016}
|
| 12 |
+
}
|
| 13 |
+
"""
|
| 14 |
+
|
| 15 |
+
_DESCRIPTION = """
|
| 16 |
+
Automatically segmented 803K SNAP Twitter Data Set hashtags with the heuristic described in the paper "Segmenting hashtags using automatically created training data".
|
| 17 |
+
"""
|
| 18 |
+
_URL = "https://raw.githubusercontent.com/ruanchaves/hashformers/master/datasets/SNAP.Hashtags.Segmented.w.Heuristics.txt"
|
| 19 |
+
|
| 20 |
+
class Snap(datasets.GeneratorBasedBuilder):
|
| 21 |
+
|
| 22 |
+
VERSION = datasets.Version("1.0.0")
|
| 23 |
+
|
| 24 |
+
def _info(self):
|
| 25 |
+
return datasets.DatasetInfo(
|
| 26 |
+
description=_DESCRIPTION,
|
| 27 |
+
features=datasets.Features(
|
| 28 |
+
{
|
| 29 |
+
"index": datasets.Value("int32"),
|
| 30 |
+
"hashtag": datasets.Value("string"),
|
| 31 |
+
"segmentation": datasets.Value("string")
|
| 32 |
+
}
|
| 33 |
+
),
|
| 34 |
+
supervised_keys=None,
|
| 35 |
+
homepage="https://github.com/ardax/hashtag-segmentor",
|
| 36 |
+
citation=_CITATION,
|
| 37 |
+
)
|
| 38 |
+
|
| 39 |
+
def _split_generators(self, dl_manager):
|
| 40 |
+
downloaded_files = dl_manager.download(_URL)
|
| 41 |
+
return [
|
| 42 |
+
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files}),
|
| 43 |
+
]
|
| 44 |
+
|
| 45 |
+
def _generate_examples(self, filepath):
|
| 46 |
+
|
| 47 |
+
with open(filepath, 'r') as f:
|
| 48 |
+
for idx, line in enumerate(f):
|
| 49 |
+
yield idx, {
|
| 50 |
+
"index": idx,
|
| 51 |
+
"hashtag": line.strip().replace(" ", ""),
|
| 52 |
+
"segmentation": line.strip()
|
| 53 |
+
}
|