Datasets:
Tasks:
Summarization
Modalities:
Text
Sub-tasks:
news-articles-summarization
Languages:
English
Size:
100K - 1M
ArXiv:
License:
Update files from the datasets library (from 1.1.3)
Browse filesRelease notes: https://github.com/huggingface/datasets/releases/tag/1.1.3
- dataset_infos.json +1 -1
- dummy/1.2.0/dummy_data.zip +3 -0
- xsum.py +67 -22
dataset_infos.json
CHANGED
@@ -1 +1 @@
|
|
1 |
-
{"default": {"description": "\nExtreme Summarization (XSum) Dataset.\n\nThere are
|
|
|
1 |
+
{"default": {"description": "\nExtreme Summarization (XSum) Dataset.\n\nThere are three features:\n - document: Input news article.\n - summary: One sentence summary of the article.\n - id: BBC ID of the article.\n\n", "citation": "\n@article{Narayan2018DontGM,\n title={Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization},\n author={Shashi Narayan and Shay B. Cohen and Mirella Lapata},\n journal={ArXiv},\n year={2018},\n volume={abs/1808.08745}\n}\n", "homepage": "https://github.com/EdinburghNLP/XSum/tree/master/XSum-Dataset", "license": "", "features": {"document": {"dtype": "string", "id": null, "_type": "Value"}, "summary": {"dtype": "string", "id": null, "_type": "Value"}, "id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": {"input": "document", "output": "summary"}, "builder_name": "xsum", "config_name": "default", "version": {"version_str": "1.2.0", "description": null, "major": 1, "minor": 2, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 479206608, "num_examples": 204045, "dataset_name": "xsum"}, "validation": {"name": "validation", "num_bytes": 26292901, "num_examples": 11332, "dataset_name": "xsum"}, "test": {"name": "test", "num_bytes": 26756165, "num_examples": 11334, "dataset_name": "xsum"}}, "download_checksums": {"http://bollin.inf.ed.ac.uk/public/direct/XSUM-EMNLP18-Summary-Data-Original.tar.gz": {"num_bytes": 254582292, "checksum": "10b48aa187fc9c904b30f76ca97e2da0de8d3a1238acc26acadef93e2001af90"}, "https://raw.githubusercontent.com/EdinburghNLP/XSum/master/XSum-Dataset/XSum-TRAINING-DEV-TEST-SPLIT-90-5-5.json": {"num_bytes": 2720574, "checksum": "9c0c5d8f048a90bd68b19a34e4c30577ed270d3247b2119fa06a04ef46292068"}}, "download_size": 257302866, "post_processing_size": null, "dataset_size": 532255674, "size_in_bytes": 789558540}}
|
dummy/1.2.0/dummy_data.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:6108aa5ec21ccb6e18ef70868eab02b335d9b59f3ac73b542e5dd3aa48993bb6
|
3 |
+
size 2943
|
xsum.py
CHANGED
@@ -18,6 +18,7 @@
|
|
18 |
|
19 |
from __future__ import absolute_import, division, print_function
|
20 |
|
|
|
21 |
import os
|
22 |
|
23 |
import datasets
|
@@ -36,25 +37,45 @@ _CITATION = """
|
|
36 |
_DESCRIPTION = """
|
37 |
Extreme Summarization (XSum) Dataset.
|
38 |
|
39 |
-
There are
|
40 |
- document: Input news article.
|
41 |
- summary: One sentence summary of the article.
|
|
|
42 |
|
43 |
"""
|
44 |
|
45 |
-
|
46 |
-
|
|
|
|
|
|
|
47 |
|
48 |
_DOCUMENT = "document"
|
49 |
_SUMMARY = "summary"
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
50 |
|
51 |
|
52 |
class Xsum(datasets.GeneratorBasedBuilder):
|
53 |
"""Extreme Summarization (XSum) Dataset."""
|
54 |
|
55 |
-
# Version 1.
|
56 |
-
VERSION = datasets.Version("1.
|
57 |
-
SUPPORTED_VERSIONS = [datasets.Version("1.0.0", "Dataset without cleaning.")]
|
58 |
|
59 |
def _info(self):
|
60 |
return datasets.DatasetInfo(
|
@@ -63,6 +84,7 @@ class Xsum(datasets.GeneratorBasedBuilder):
|
|
63 |
{
|
64 |
_DOCUMENT: datasets.Value("string"),
|
65 |
_SUMMARY: datasets.Value("string"),
|
|
|
66 |
}
|
67 |
),
|
68 |
supervised_keys=(_DOCUMENT, _SUMMARY),
|
@@ -73,39 +95,62 @@ class Xsum(datasets.GeneratorBasedBuilder):
|
|
73 |
def _split_generators(self, dl_manager):
|
74 |
"""Returns SplitGenerators."""
|
75 |
|
76 |
-
|
|
|
77 |
|
78 |
-
dl_path = os.path.join(dl_path, "xsum")
|
79 |
return [
|
80 |
datasets.SplitGenerator(
|
81 |
name=datasets.Split.TRAIN,
|
82 |
gen_kwargs={
|
83 |
-
"
|
84 |
-
"
|
|
|
85 |
},
|
86 |
),
|
87 |
datasets.SplitGenerator(
|
88 |
name=datasets.Split.VALIDATION,
|
89 |
gen_kwargs={
|
90 |
-
"
|
91 |
-
"
|
|
|
92 |
},
|
93 |
),
|
94 |
datasets.SplitGenerator(
|
95 |
name=datasets.Split.TEST,
|
96 |
gen_kwargs={
|
97 |
-
"
|
98 |
-
"
|
|
|
99 |
},
|
100 |
),
|
101 |
]
|
102 |
|
103 |
-
def _generate_examples(self,
|
104 |
"""Yields examples."""
|
105 |
-
|
106 |
-
|
107 |
-
|
108 |
-
|
109 |
-
|
110 |
-
|
111 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
18 |
|
19 |
from __future__ import absolute_import, division, print_function
|
20 |
|
21 |
+
import json
|
22 |
import os
|
23 |
|
24 |
import datasets
|
|
|
37 |
_DESCRIPTION = """
|
38 |
Extreme Summarization (XSum) Dataset.
|
39 |
|
40 |
+
There are three features:
|
41 |
- document: Input news article.
|
42 |
- summary: One sentence summary of the article.
|
43 |
+
- id: BBC ID of the article.
|
44 |
|
45 |
"""
|
46 |
|
47 |
+
# From https://github.com/EdinburghNLP/XSum/issues/12
|
48 |
+
_URL_DATA = "http://bollin.inf.ed.ac.uk/public/direct/XSUM-EMNLP18-Summary-Data-Original.tar.gz"
|
49 |
+
_URL_SPLITS = (
|
50 |
+
"https://raw.githubusercontent.com/EdinburghNLP/XSum/master/XSum-Dataset/XSum-TRAINING-DEV-TEST-SPLIT-90-5-5.json"
|
51 |
+
)
|
52 |
|
53 |
_DOCUMENT = "document"
|
54 |
_SUMMARY = "summary"
|
55 |
+
_ID = "id"
|
56 |
+
|
57 |
+
_REMOVE_LINES = set(
|
58 |
+
[
|
59 |
+
"Share this with\n",
|
60 |
+
"Email\n",
|
61 |
+
"Facebook\n",
|
62 |
+
"Messenger\n",
|
63 |
+
"Twitter\n",
|
64 |
+
"Pinterest\n",
|
65 |
+
"WhatsApp\n",
|
66 |
+
"Linkedin\n",
|
67 |
+
"LinkedIn\n",
|
68 |
+
"Copy this link\n",
|
69 |
+
"These are external links and will open in a new window\n",
|
70 |
+
]
|
71 |
+
)
|
72 |
|
73 |
|
74 |
class Xsum(datasets.GeneratorBasedBuilder):
|
75 |
"""Extreme Summarization (XSum) Dataset."""
|
76 |
|
77 |
+
# Version 1.2.0 expands coverage, includes ids, and removes web contents.
|
78 |
+
VERSION = datasets.Version("1.2.0")
|
|
|
79 |
|
80 |
def _info(self):
|
81 |
return datasets.DatasetInfo(
|
|
|
84 |
{
|
85 |
_DOCUMENT: datasets.Value("string"),
|
86 |
_SUMMARY: datasets.Value("string"),
|
87 |
+
_ID: datasets.Value("string"),
|
88 |
}
|
89 |
),
|
90 |
supervised_keys=(_DOCUMENT, _SUMMARY),
|
|
|
95 |
def _split_generators(self, dl_manager):
|
96 |
"""Returns SplitGenerators."""
|
97 |
|
98 |
+
files_to_download = {"data": _URL_DATA, "splits": _URL_SPLITS}
|
99 |
+
downloaded_files = dl_manager.download_and_extract(files_to_download)
|
100 |
|
|
|
101 |
return [
|
102 |
datasets.SplitGenerator(
|
103 |
name=datasets.Split.TRAIN,
|
104 |
gen_kwargs={
|
105 |
+
"split_path": downloaded_files["splits"],
|
106 |
+
"split_name": "train",
|
107 |
+
"data_dir": os.path.join(downloaded_files["data"], "bbc-summary-data"),
|
108 |
},
|
109 |
),
|
110 |
datasets.SplitGenerator(
|
111 |
name=datasets.Split.VALIDATION,
|
112 |
gen_kwargs={
|
113 |
+
"split_path": downloaded_files["splits"],
|
114 |
+
"split_name": "validation",
|
115 |
+
"data_dir": os.path.join(downloaded_files["data"], "bbc-summary-data"),
|
116 |
},
|
117 |
),
|
118 |
datasets.SplitGenerator(
|
119 |
name=datasets.Split.TEST,
|
120 |
gen_kwargs={
|
121 |
+
"split_path": downloaded_files["splits"],
|
122 |
+
"split_name": "test",
|
123 |
+
"data_dir": os.path.join(downloaded_files["data"], "bbc-summary-data"),
|
124 |
},
|
125 |
),
|
126 |
]
|
127 |
|
128 |
+
def _generate_examples(self, split_path, split_name, data_dir):
|
129 |
"""Yields examples."""
|
130 |
+
|
131 |
+
with open(split_path, "r", encoding="utf-8") as f:
|
132 |
+
split_ids = json.load(f)
|
133 |
+
|
134 |
+
for i in split_ids[split_name]:
|
135 |
+
with open(os.path.join(data_dir, i + ".summary"), "r", encoding="utf-8") as f:
|
136 |
+
text = "".join([line for line in f.readlines() if line not in _REMOVE_LINES and line.strip()])
|
137 |
+
# Each file follows below format:
|
138 |
+
# [SN]URL[SN]
|
139 |
+
# http://somelink
|
140 |
+
#
|
141 |
+
# [SN]TITLE[SN]
|
142 |
+
# some intro
|
143 |
+
#
|
144 |
+
# [SN]FIRST-SENTENCE[SN]
|
145 |
+
# some intro
|
146 |
+
#
|
147 |
+
# [SN]RESTBODY[SN]
|
148 |
+
# text line.
|
149 |
+
# another text line.
|
150 |
+
# "another text line."
|
151 |
+
|
152 |
+
# According to the following issue, FIRST-SENTENCE
|
153 |
+
# is the reference summary and TITLE is unused:
|
154 |
+
# https://github.com/EdinburghNLP/XSum/issues/22
|
155 |
+
segs = text.split("[SN]")
|
156 |
+
yield i, {_DOCUMENT: segs[8].strip(), _SUMMARY: segs[6].strip(), _ID: i}
|