Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
multi-class-classification
Languages:
English
Size:
100K - 1M
License:
Commit
•
e90c21e
1
Parent(s):
df64003
Delete loading script
Browse files- coarse_discourse.py +0 -116
coarse_discourse.py
DELETED
@@ -1,116 +0,0 @@
|
|
1 |
-
"""TODO(coarse_discourse): Add a description here."""
|
2 |
-
|
3 |
-
|
4 |
-
import json
|
5 |
-
|
6 |
-
import datasets
|
7 |
-
|
8 |
-
|
9 |
-
# TODO(coarse_discourse): BibTeX citation
|
10 |
-
_CITATION = """\
|
11 |
-
@inproceedings{coarsediscourse, title={Characterizing Online Discussion Using Coarse Discourse Sequences}, author={Zhang, Amy X. and Culbertson, Bryan and Paritosh, Praveen}, booktitle={Proceedings of the 11th International AAAI Conference on Weblogs and Social Media}, series={ICWSM '17}, year={2017}, location = {Montreal, Canada} }
|
12 |
-
"""
|
13 |
-
|
14 |
-
# TODO(coarse_discourse):
|
15 |
-
_DESCRIPTION = """\
|
16 |
-
dataset contains discourse annotation and relation on threads from reddit during 2016
|
17 |
-
"""
|
18 |
-
# From: https://github.com/google-research-datasets/coarse-discourse
|
19 |
-
_URL = "https://raw.githubusercontent.com/google-research-datasets/coarse-discourse/master/coarse_discourse_dataset.json"
|
20 |
-
|
21 |
-
|
22 |
-
class CoarseDiscourse(datasets.GeneratorBasedBuilder):
|
23 |
-
"""TODO(coarse_discourse): Short description of my dataset."""
|
24 |
-
|
25 |
-
# TODO(coarse_discourse): Set up version.
|
26 |
-
VERSION = datasets.Version("0.1.0")
|
27 |
-
|
28 |
-
def _info(self):
|
29 |
-
# TODO(coarse_discourse): Specifies the datasets.DatasetInfo object
|
30 |
-
return datasets.DatasetInfo(
|
31 |
-
# This is the description that will appear on the datasets page.
|
32 |
-
description=_DESCRIPTION,
|
33 |
-
# datasets.features.FeatureConnectors
|
34 |
-
features=datasets.Features(
|
35 |
-
{
|
36 |
-
# These are the features of your dataset like images, labels ...
|
37 |
-
"title": datasets.Value("string"),
|
38 |
-
"is_self_post": datasets.Value("bool"),
|
39 |
-
"subreddit": datasets.Value("string"),
|
40 |
-
"url": datasets.Value("string"),
|
41 |
-
"majority_link": datasets.Value("string"),
|
42 |
-
"is_first_post": datasets.Value("bool"),
|
43 |
-
"majority_type": datasets.Value("string"),
|
44 |
-
"id_post": datasets.Value("string"),
|
45 |
-
"post_depth": datasets.Value("int32"),
|
46 |
-
"in_reply_to": datasets.Value("string"),
|
47 |
-
"annotations": datasets.features.Sequence(
|
48 |
-
{
|
49 |
-
"annotator": datasets.Value("string"),
|
50 |
-
"link_to_post": datasets.Value("string"),
|
51 |
-
"main_type": datasets.Value("string"),
|
52 |
-
}
|
53 |
-
),
|
54 |
-
}
|
55 |
-
),
|
56 |
-
# If there's a common (input, target) tuple from the features,
|
57 |
-
# specify them here. They'll be used if as_supervised=True in
|
58 |
-
# builder.as_dataset.
|
59 |
-
supervised_keys=None,
|
60 |
-
# Homepage of the dataset for documentation
|
61 |
-
homepage="https://github.com/google-research-datasets/coarse-discourse",
|
62 |
-
citation=_CITATION,
|
63 |
-
)
|
64 |
-
|
65 |
-
def _split_generators(self, dl_manager):
|
66 |
-
"""Returns SplitGenerators."""
|
67 |
-
# TODO(coarse_discourse): Downloads the data and defines the splits
|
68 |
-
# dl_manager is a datasets.download.DownloadManager that can be used to
|
69 |
-
# download and extract URLs
|
70 |
-
data_path = dl_manager.download(_URL)
|
71 |
-
return [
|
72 |
-
datasets.SplitGenerator(
|
73 |
-
name=datasets.Split.TRAIN,
|
74 |
-
# These kwargs will be passed to _generate_examples
|
75 |
-
gen_kwargs={
|
76 |
-
"filepath": data_path,
|
77 |
-
},
|
78 |
-
),
|
79 |
-
]
|
80 |
-
|
81 |
-
def _generate_examples(self, filepath):
|
82 |
-
"""Yields examples."""
|
83 |
-
# TODO(coarse_discourse): Yields (key, example) tuples from the dataset
|
84 |
-
with open(filepath, encoding="utf-8") as f:
|
85 |
-
for id_, row in enumerate(f):
|
86 |
-
data = json.loads(row)
|
87 |
-
url = data.get("url", "")
|
88 |
-
is_self_post = data.get("is_self_post", "")
|
89 |
-
subreddit = data.get("subreddit", "")
|
90 |
-
title = data.get("title", "")
|
91 |
-
posts = data.get("posts", "")
|
92 |
-
for id1, post in enumerate(posts):
|
93 |
-
maj_link = post.get("majority_link", "")
|
94 |
-
maj_type = post.get("majority_type", "")
|
95 |
-
id_post = post.get("id", "")
|
96 |
-
is_first_post = post.get("is_firs_post", "")
|
97 |
-
post_depth = post.get("post_depth", -1)
|
98 |
-
in_reply_to = post.get("in_reply_to", "")
|
99 |
-
annotations = post["annotations"]
|
100 |
-
annotators = [annotation.get("annotator", "") for annotation in annotations]
|
101 |
-
main_types = [annotation.get("main_type", "") for annotation in annotations]
|
102 |
-
link_posts = [annotation.get("linkk_to_post", "") for annotation in annotations]
|
103 |
-
|
104 |
-
yield str(id_) + "_" + str(id1), {
|
105 |
-
"title": title,
|
106 |
-
"is_self_post": is_self_post,
|
107 |
-
"subreddit": subreddit,
|
108 |
-
"url": url,
|
109 |
-
"majority_link": maj_link,
|
110 |
-
"is_first_post": is_first_post,
|
111 |
-
"majority_type": maj_type,
|
112 |
-
"id_post": id_post,
|
113 |
-
"post_depth": post_depth,
|
114 |
-
"in_reply_to": in_reply_to,
|
115 |
-
"annotations": {"annotator": annotators, "link_to_post": link_posts, "main_type": main_types},
|
116 |
-
}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|