hojjat-m commited on
Commit
ae2bb3b
1 Parent(s): 135883e

data files added

Browse files
Files changed (4) hide show
  1. PEYMA.py +0 -79
  2. data/dev.txt +0 -0
  3. data/test.txt +0 -0
  4. data/train.txt +0 -0
PEYMA.py DELETED
@@ -1,79 +0,0 @@
1
- import json
2
- import pandas as pd
3
- import datasets
4
- import requests
5
- import os
6
-
7
- _CITATION = """\\
8
- @article{shahshahani2018peyma,
9
- title={PEYMA: A Tagged Corpus for Persian Named Entities},
10
- author={Mahsa Sadat Shahshahani and Mahdi Mohseni and Azadeh Shakery and Heshaam Faili},
11
- year=2018,
12
- journal={ArXiv},
13
- volume={abs/1801.09936}
14
- }
15
- """
16
- _DESCRIPTION = """\\\\\\\\
17
- PEYMA dataset includes 7,145 sentences with a total of 302,530 tokens from which 41,148 tokens are tagged with seven different classes.
18
- """
19
-
20
- _DRIVE_URL = "https://drive.google.com/uc?export=download&id=1WZxpFRtEs5HZWyWQ2Pyg9CCuIBs1Kmvx"
21
-
22
- class PEYMAConfig(datasets.BuilderConfig):
23
- """BuilderConfig for PEYMA."""
24
- def __init__(self, **kwargs):
25
- super(PEYMAConfig, self).__init__(**kwargs)
26
-
27
- class PEYMA(datasets.GeneratorBasedBuilder):
28
- BUILDER_CONFIGS = [
29
- PEYMAConfig(name="PEYMA", version=datasets.Version("1.0.0"), description="persian ner dataset"),
30
- ]
31
- def _info(self):
32
- return datasets.DatasetInfo(
33
- # This is the description that will appear on the datasets page.
34
- description=_DESCRIPTION,
35
- # datasets.features.FeatureConnectors
36
- features=datasets.Features(
37
- {
38
- "token": datasets.Value("string"),
39
- "label": datasets.Value("string")
40
- }
41
- ),
42
- supervised_keys=None,
43
- # Homepage of the dataset for documentation
44
- homepage="https://hooshvare.github.io/docs/datasets/ner#peyma",
45
- citation=_CITATION,
46
- )
47
-
48
- def custom_dataset(self, src_url, dest_path):
49
- response = requests.get(src_url)
50
- response.raise_for_status()
51
-
52
- with open(dest_path, 'wb') as f:
53
- f.write(response.content)
54
-
55
-
56
- def _split_generators(self, dl_manager):
57
- """Returns SplitGenerators."""
58
- # dl_manager is a datasets.download.DownloadManager that can be used to
59
- # download and extract URLs
60
-
61
- downloaded_file = dl_manager.download_custom(_DRIVE_URL, self.custom_dataset)
62
- extracted_file = dl_manager.extract(downloaded_file)
63
- return [
64
- datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": os.path.join(extracted_file, 'peyma/train.txt')}),
65
- datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": os.path.join(extracted_file, 'peyma/test.txt')}),
66
- datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": os.path.join(extracted_file, 'peyma/dev.txt')}),
67
- ]
68
-
69
- def _generate_examples(self, filepath):
70
- try:
71
- df = pd.read_csv(filepath, error_bad_lines=False, engine='python',
72
- sep='|', names=["token", "label"])
73
- for idx, row in enumerate(reader):
74
- yield idx, {
75
- "token": row["token"],
76
- "label": row["label"]
77
- }
78
- except Exception as e:
79
- print(e)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
data/dev.txt ADDED
The diff for this file is too large to render. See raw diff
 
data/test.txt ADDED
The diff for this file is too large to render. See raw diff
 
data/train.txt ADDED
The diff for this file is too large to render. See raw diff