Add complex_web_questions.py
Browse files- complex_web_questions.py +144 -0
complex_web_questions.py
ADDED
|
@@ -0,0 +1,144 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
"""ComplexWebQuestions: A Dataset for Answering Complex Questions that Require Reasoning over Multiple Web Snippets."""
|
| 2 |
+
|
| 3 |
+
import json
|
| 4 |
+
import os
|
| 5 |
+
|
| 6 |
+
import datasets
|
| 7 |
+
|
| 8 |
+
logger = datasets.logging.get_logger(__name__)
|
| 9 |
+
|
| 10 |
+
_CITATION = """\
|
| 11 |
+
@inproceedings{Talmor2018TheWA,
|
| 12 |
+
title={The Web as a Knowledge-Base for Answering Complex Questions},
|
| 13 |
+
author={Alon Talmor and Jonathan Berant},
|
| 14 |
+
booktitle={NAACL},
|
| 15 |
+
year={2018}
|
| 16 |
+
}
|
| 17 |
+
"""
|
| 18 |
+
|
| 19 |
+
_DESCRIPTION = """\
|
| 20 |
+
ComplexWebQuestions is a dataset for answering complex questions that require reasoning over multiple web snippets. It contains a large set of complex questions in natural language, and can be used in multiple ways: 1) By interacting with a search engine, which is the focus of our paper (Talmor and Berant, 2018); 2) As a reading comprehension task: we release 12,725,989 web snippets that are relevant for the questions, and were collected during the development of our model; 3) As a semantic parsing task: each question is paired with a SPARQL query that can be executed against Freebase to retrieve the answer.
|
| 21 |
+
"""
|
| 22 |
+
|
| 23 |
+
_URL = "https://allenai.org/data/complexwebquestions"
|
| 24 |
+
_COMPLEXWEBQUESTIONS_URLS = {
|
| 25 |
+
"train": "https://www.dropbox.com/sh/7pkwkrfnwqhsnpo/AAAIHeWX0cPpbpwK6w06BCxva/ComplexWebQuestions_train.json?dl=1",
|
| 26 |
+
"dev": "https://www.dropbox.com/sh/7pkwkrfnwqhsnpo/AADH8beLbOUWxwvY_K38E3ADa/ComplexWebQuestions_dev.json?dl=1",
|
| 27 |
+
"test": "https://www.dropbox.com/sh/7pkwkrfnwqhsnpo/AABr4ysSy_Tg8Wfxww4i_UWda/ComplexWebQuestions_test.json?dl=1"
|
| 28 |
+
}
|
| 29 |
+
|
| 30 |
+
class ComplexWebQuestionsConfig(datasets.BuilderConfig):
|
| 31 |
+
"""BuilderConfig for ComplexWebQuestions"""
|
| 32 |
+
def __init__(self,
|
| 33 |
+
data_url,
|
| 34 |
+
data_dir,
|
| 35 |
+
**kwargs):
|
| 36 |
+
"""BuilderConfig for ComplexWebQuestions.
|
| 37 |
+
Args:
|
| 38 |
+
**kwargs: keyword arguments forwarded to super.
|
| 39 |
+
"""
|
| 40 |
+
super(ComplexWebQuestionsConfig, self).__init__(**kwargs)
|
| 41 |
+
self.data_url = data_url
|
| 42 |
+
self.data_dir = data_dir
|
| 43 |
+
|
| 44 |
+
class ComplexWebQuestions(datasets.GeneratorBasedBuilder):
|
| 45 |
+
"""ComplexWebQuestions: A Dataset for Answering Complex Questions that Require Reasoning over Multiple Web Snippets."""
|
| 46 |
+
BUILDER_CONFIGS = [
|
| 47 |
+
ComplexWebQuestionsConfig(
|
| 48 |
+
name="complex_web_questions",
|
| 49 |
+
description="ComplexWebQuestions",
|
| 50 |
+
data_url="",
|
| 51 |
+
data_dir="ComplexWebQuestions"
|
| 52 |
+
),
|
| 53 |
+
ComplexWebQuestionsConfig(
|
| 54 |
+
name="complexwebquestions_test",
|
| 55 |
+
description="ComplexWebQuestions",
|
| 56 |
+
data_url="",
|
| 57 |
+
data_dir="ComplexWebQuestions"
|
| 58 |
+
)
|
| 59 |
+
]
|
| 60 |
+
|
| 61 |
+
def _info(self):
|
| 62 |
+
features = datasets.Features(
|
| 63 |
+
{
|
| 64 |
+
"ID": datasets.Value("string"),
|
| 65 |
+
"answers": datasets.features.Sequence(
|
| 66 |
+
datasets.Features(
|
| 67 |
+
{
|
| 68 |
+
"aliases": datasets.features.Sequence(
|
| 69 |
+
datasets.Value("string")
|
| 70 |
+
),
|
| 71 |
+
"answer": datasets.Value("string"),
|
| 72 |
+
"answer_id": datasets.Value("string")
|
| 73 |
+
}
|
| 74 |
+
)
|
| 75 |
+
),
|
| 76 |
+
"composition_answer": datasets.Value("string"),
|
| 77 |
+
"compositionality_type": datasets.Value("string"),
|
| 78 |
+
"created": datasets.Value("string"),
|
| 79 |
+
"machine_question": datasets.Value("string"),
|
| 80 |
+
"question": datasets.Value("string"),
|
| 81 |
+
"sparql": datasets.Value("string"),
|
| 82 |
+
"webqsp_ID": datasets.Value("string"),
|
| 83 |
+
"webqsp_question": datasets.Value("string")
|
| 84 |
+
}
|
| 85 |
+
)
|
| 86 |
+
|
| 87 |
+
if self.config.name == "complexwebquestions_test":
|
| 88 |
+
features.pop("answers", None)
|
| 89 |
+
features.pop("composition_answer", None)
|
| 90 |
+
|
| 91 |
+
return datasets.DatasetInfo(
|
| 92 |
+
description=_DESCRIPTION,
|
| 93 |
+
supervised_keys=None,
|
| 94 |
+
homepage=_URL,
|
| 95 |
+
citation=_CITATION,
|
| 96 |
+
features=features
|
| 97 |
+
)
|
| 98 |
+
|
| 99 |
+
def _split_generators(self, dl_manager):
|
| 100 |
+
data_dir = None
|
| 101 |
+
if self.config.name == "complexwebquestions_test":
|
| 102 |
+
complexwebquestions_test_files = dl_manager.download(
|
| 103 |
+
{
|
| 104 |
+
"test": _COMPLEXWEBQUESTIONS_URLS["test"],
|
| 105 |
+
}
|
| 106 |
+
)
|
| 107 |
+
return [
|
| 108 |
+
datasets.SplitGenerator(
|
| 109 |
+
name=datasets.Split.TEST,
|
| 110 |
+
gen_kwargs={
|
| 111 |
+
"data_file": os.path.join(data_dir or "", complexwebquestions_test_files["test"]),
|
| 112 |
+
"split": "test"
|
| 113 |
+
}
|
| 114 |
+
)
|
| 115 |
+
]
|
| 116 |
+
else:
|
| 117 |
+
complexwebquestions_files = dl_manager.download(
|
| 118 |
+
{
|
| 119 |
+
"train": _COMPLEXWEBQUESTIONS_URLS["train"],
|
| 120 |
+
"dev": _COMPLEXWEBQUESTIONS_URLS["dev"]
|
| 121 |
+
}
|
| 122 |
+
)
|
| 123 |
+
return [
|
| 124 |
+
datasets.SplitGenerator(
|
| 125 |
+
name=datasets.Split.TRAIN,
|
| 126 |
+
gen_kwargs={
|
| 127 |
+
"data_file": os.path.join(data_dir or "", complexwebquestions_files["train"]),
|
| 128 |
+
"split": "train"
|
| 129 |
+
}
|
| 130 |
+
),
|
| 131 |
+
datasets.SplitGenerator(
|
| 132 |
+
name=datasets.Split.VALIDATION,
|
| 133 |
+
gen_kwargs={
|
| 134 |
+
"data_file": os.path.join(data_dir or "", complexwebquestions_files["dev"]),
|
| 135 |
+
"split": "validation"
|
| 136 |
+
}
|
| 137 |
+
)
|
| 138 |
+
]
|
| 139 |
+
|
| 140 |
+
def _generate_examples(self, data_file, **kwargs):
|
| 141 |
+
with open(data_file, encoding="utf8") as f:
|
| 142 |
+
complexwebquestions = json.load(f)
|
| 143 |
+
for idx, question in enumerate(complexwebquestions):
|
| 144 |
+
yield idx, question
|