Datasets:
Tasks:
Question Answering
Modalities:
Text
Formats:
parquet
Sub-tasks:
open-domain-qa
Languages:
English
Size:
10K - 100K
License:
Commit
•
df3247d
0
Parent(s):
Update files from the datasets library (from 1.0.0)
Browse filesRelease notes: https://github.com/huggingface/datasets/releases/tag/1.0.0
- .gitattributes +27 -0
- dataset_infos.json +1 -0
- dummy/0.1.0/dummy_data.zip +3 -0
- wiki_qa.py +97 -0
.gitattributes
ADDED
@@ -0,0 +1,27 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
*.7z filter=lfs diff=lfs merge=lfs -text
|
2 |
+
*.arrow filter=lfs diff=lfs merge=lfs -text
|
3 |
+
*.bin filter=lfs diff=lfs merge=lfs -text
|
4 |
+
*.bin.* filter=lfs diff=lfs merge=lfs -text
|
5 |
+
*.bz2 filter=lfs diff=lfs merge=lfs -text
|
6 |
+
*.ftz filter=lfs diff=lfs merge=lfs -text
|
7 |
+
*.gz filter=lfs diff=lfs merge=lfs -text
|
8 |
+
*.h5 filter=lfs diff=lfs merge=lfs -text
|
9 |
+
*.joblib filter=lfs diff=lfs merge=lfs -text
|
10 |
+
*.lfs.* filter=lfs diff=lfs merge=lfs -text
|
11 |
+
*.model filter=lfs diff=lfs merge=lfs -text
|
12 |
+
*.msgpack filter=lfs diff=lfs merge=lfs -text
|
13 |
+
*.onnx filter=lfs diff=lfs merge=lfs -text
|
14 |
+
*.ot filter=lfs diff=lfs merge=lfs -text
|
15 |
+
*.parquet filter=lfs diff=lfs merge=lfs -text
|
16 |
+
*.pb filter=lfs diff=lfs merge=lfs -text
|
17 |
+
*.pt filter=lfs diff=lfs merge=lfs -text
|
18 |
+
*.pth filter=lfs diff=lfs merge=lfs -text
|
19 |
+
*.rar filter=lfs diff=lfs merge=lfs -text
|
20 |
+
saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
21 |
+
*.tar.* filter=lfs diff=lfs merge=lfs -text
|
22 |
+
*.tflite filter=lfs diff=lfs merge=lfs -text
|
23 |
+
*.tgz filter=lfs diff=lfs merge=lfs -text
|
24 |
+
*.xz filter=lfs diff=lfs merge=lfs -text
|
25 |
+
*.zip filter=lfs diff=lfs merge=lfs -text
|
26 |
+
*.zstandard filter=lfs diff=lfs merge=lfs -text
|
27 |
+
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
dataset_infos.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"default": {"description": "Wiki Question Answering corpus from Microsoft\n", "citation": "@InProceedings{YangYihMeek:EMNLP2015:WikiQA,\n author = {{Yi}, Yang and {Wen-tau}, Yih and {Christopher} Meek},\n title = \"{WikiQA: A Challenge Dataset for Open-Domain Question Answering}\",\n journal = {Association for Computational Linguistics},\n year = 2015,\n doi = {10.18653/v1/D15-1237},\n pages = {2013\u20132018},\n}\n", "homepage": "https://www.microsoft.com/en-us/download/details.aspx?id=52419", "license": "", "features": {"question_id": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "document_title": {"dtype": "string", "id": null, "_type": "Value"}, "answer": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 2, "names": ["0", "1"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "supervised_keys": null, "builder_name": "wiki_qa", "config_name": "default", "version": {"version_str": "0.1.0", "description": null, "datasets_version_to_prepare": null, "major": 0, "minor": 1, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 1337903, "num_examples": 6165, "dataset_name": "wiki_qa"}, "train": {"name": "train", "num_bytes": 4469148, "num_examples": 20360, "dataset_name": "wiki_qa"}, "validation": {"name": "validation", "num_bytes": 591833, "num_examples": 2733, "dataset_name": "wiki_qa"}}, "download_checksums": {"https://download.microsoft.com/download/E/5/f/E5FCFCEE-7005-4814-853D-DAA7C66507E0/WikiQACorpus.zip": {"num_bytes": 7094233, "checksum": "467c13f9e104552c0a9c16f41836ca8d89f9c0cc4b6e4355e104d5c3109ffa45"}}, "download_size": 7094233, "dataset_size": 6398884, "size_in_bytes": 13493117}}
|
dummy/0.1.0/dummy_data.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:8d7238a3a8d7e6f18ef01eacdb01fdcd3ba855fbf9c95b9e30040c488301a741
|
3 |
+
size 1766
|
wiki_qa.py
ADDED
@@ -0,0 +1,97 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
"""TODO(wiki_qa): Add a description here."""
|
2 |
+
|
3 |
+
from __future__ import absolute_import, division, print_function
|
4 |
+
|
5 |
+
import csv
|
6 |
+
import os
|
7 |
+
|
8 |
+
import datasets
|
9 |
+
|
10 |
+
|
11 |
+
# TODO(wiki_qa): BibTeX citation
|
12 |
+
_CITATION = """\
|
13 |
+
@InProceedings{YangYihMeek:EMNLP2015:WikiQA,
|
14 |
+
author = {{Yi}, Yang and {Wen-tau}, Yih and {Christopher} Meek},
|
15 |
+
title = "{WikiQA: A Challenge Dataset for Open-Domain Question Answering}",
|
16 |
+
journal = {Association for Computational Linguistics},
|
17 |
+
year = 2015,
|
18 |
+
doi = {10.18653/v1/D15-1237},
|
19 |
+
pages = {2013–2018},
|
20 |
+
}
|
21 |
+
"""
|
22 |
+
|
23 |
+
# TODO(wiki_qa):
|
24 |
+
_DESCRIPTION = """\
|
25 |
+
Wiki Question Answering corpus from Microsoft
|
26 |
+
"""
|
27 |
+
|
28 |
+
_DATA_URL = "https://download.microsoft.com/download/E/5/f/E5FCFCEE-7005-4814-853D-DAA7C66507E0/WikiQACorpus.zip" # 'https://www.microsoft.com/en-us/download/confirmation.aspx?id=52419'
|
29 |
+
|
30 |
+
|
31 |
+
class WikiQa(datasets.GeneratorBasedBuilder):
|
32 |
+
"""TODO(wiki_qa): Short description of my dataset."""
|
33 |
+
|
34 |
+
# TODO(wiki_qa): Set up version.
|
35 |
+
VERSION = datasets.Version("0.1.0")
|
36 |
+
|
37 |
+
def _info(self):
|
38 |
+
# TODO(wiki_qa): Specifies the datasets.DatasetInfo object
|
39 |
+
return datasets.DatasetInfo(
|
40 |
+
# This is the description that will appear on the datasets page.
|
41 |
+
description=_DESCRIPTION,
|
42 |
+
# datasets.features.FeatureConnectors
|
43 |
+
features=datasets.Features(
|
44 |
+
{
|
45 |
+
"question_id": datasets.Value("string"),
|
46 |
+
"question": datasets.Value("string"),
|
47 |
+
"document_title": datasets.Value("string"),
|
48 |
+
"answer": datasets.Value("string"),
|
49 |
+
"label": datasets.features.ClassLabel(num_classes=2),
|
50 |
+
# These are the features of your dataset like images, labels ...
|
51 |
+
}
|
52 |
+
),
|
53 |
+
# If there's a common (input, target) tuple from the features,
|
54 |
+
# specify them here. They'll be used if as_supervised=True in
|
55 |
+
# builder.as_dataset.
|
56 |
+
supervised_keys=None,
|
57 |
+
# Homepage of the dataset for documentation
|
58 |
+
homepage="https://www.microsoft.com/en-us/download/details.aspx?id=52419",
|
59 |
+
citation=_CITATION,
|
60 |
+
)
|
61 |
+
|
62 |
+
def _split_generators(self, dl_manager):
|
63 |
+
"""Returns SplitGenerators."""
|
64 |
+
# TODO(wiki_qa): Downloads the data and defines the splits
|
65 |
+
# dl_manager is a datasets.download.DownloadManager that can be used to
|
66 |
+
# download and extract URLs
|
67 |
+
dl_dir = dl_manager.download_and_extract(_DATA_URL)
|
68 |
+
dl_dir = os.path.join(dl_dir, "WikiQACorpus")
|
69 |
+
# dl_dir = os.path.join(dl_dir, '')
|
70 |
+
return [
|
71 |
+
datasets.SplitGenerator(
|
72 |
+
name=datasets.Split.TEST, gen_kwargs={"filepath": os.path.join(dl_dir, "WikiQA-test.tsv")}
|
73 |
+
),
|
74 |
+
datasets.SplitGenerator(
|
75 |
+
name=datasets.Split.VALIDATION, gen_kwargs={"filepath": os.path.join(dl_dir, "WikiQA-dev.tsv")}
|
76 |
+
),
|
77 |
+
datasets.SplitGenerator(
|
78 |
+
name=datasets.Split.TRAIN,
|
79 |
+
# These kwargs will be passed to _generate_examples
|
80 |
+
gen_kwargs={"filepath": os.path.join(dl_dir, "WikiQA-train.tsv")},
|
81 |
+
),
|
82 |
+
]
|
83 |
+
|
84 |
+
def _generate_examples(self, filepath):
|
85 |
+
"""Yields examples."""
|
86 |
+
# TODO(wiki_qa): Yields (key, example) tuples from the dataset
|
87 |
+
|
88 |
+
with open(filepath, encoding="utf-8") as f:
|
89 |
+
reader = csv.DictReader(f, delimiter="\t", quoting=csv.QUOTE_NONE)
|
90 |
+
for idx, row in enumerate(reader):
|
91 |
+
yield idx, {
|
92 |
+
"question_id": row["QuestionID"],
|
93 |
+
"question": row["Question"],
|
94 |
+
"document_title": row["DocumentTitle"],
|
95 |
+
"answer": row["Sentence"],
|
96 |
+
"label": row["Label"],
|
97 |
+
}
|