Datasets:
Sub-tasks:
dialogue-modeling
Languages:
Chinese
Multilinguality:
monolingual
Size Categories:
1K<n<10K
Language Creators:
crowdsourced
Source Datasets:
original
Tags:
License:
File size: 7,881 Bytes
9c8827c 84a4566 9c8827c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 |
# coding=utf-8
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""KdConv: Chinese multi-domain Knowledge-driven Conversionsation dataset"""
import json
import os
import datasets
_CITATION = """\
@inproceedings{zhou-etal-2020-kdconv,
title = "{K}d{C}onv: A {C}hinese Multi-domain Dialogue Dataset Towards Multi-turn Knowledge-driven Conversation",
author = "Zhou, Hao and
Zheng, Chujie and
Huang, Kaili and
Huang, Minlie and
Zhu, Xiaoyan",
booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
month = jul,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/2020.acl-main.635",
doi = "10.18653/v1/2020.acl-main.635",
pages = "7098--7108",
}
"""
_DESCRIPTION = """\
KdConv is a Chinese multi-domain Knowledge-driven Conversionsation dataset, grounding the topics in multi-turn \
conversations to knowledge graphs. KdConv contains 4.5K conversations from three domains (film, music, and travel), \
and 86K utterances with an average turn number of 19.0. These conversations contain in-depth discussions on related \
topics and natural transition between multiple topics, while the corpus can also used for exploration of transfer \
learning and domain adaptation.\
"""
_HOMEPAGE = "https://github.com/thu-coai/KdConv"
_LICENSE = "Apache License 2.0"
_URL = "https://github.com/thu-coai/KdConv/archive/master.zip"
_DOMAINS = ["travel", "music", "film"]
_DATA_TYPES = ["dialogues", "knowledge_base"]
class KdConv(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("1.1.0")
BUILDER_CONFIGS = [
datasets.BuilderConfig(
name=domain + "_" + type,
description="This part of dataset covers {0} domain and {1} data " "of the corpus".format(domain, type),
)
for domain in _DOMAINS
for type in _DATA_TYPES
] + [
datasets.BuilderConfig(
name="all_" + type,
description="This part of dataset covers all domains and {0} data of " "the corpus".format(type),
)
for type in _DATA_TYPES
]
DEFAULT_CONFIG_NAME = "all_dialogues"
def _info(self):
if "dialogues" in self.config.name:
features = datasets.Features(
{
"messages": datasets.Sequence(
{
"message": datasets.Value("string"),
"attrs": datasets.Sequence(
{
"attrname": datasets.Value("string"),
"attrvalue": datasets.Value("string"),
"name": datasets.Value("string"),
}
),
}
),
"name": datasets.Value("string"),
"domain": datasets.Value("string"),
}
)
else:
features = datasets.Features(
{
"head_entity": datasets.Value("string"),
"kb_triplets": datasets.Sequence(datasets.Sequence(datasets.Value("string"))),
"domain": datasets.Value("string"),
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
supervised_keys=None,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
data_dir = dl_manager.download_and_extract(_URL)
base_dir = os.path.join(os.path.join(data_dir, "KdConv-master"), "data")
if "dialogues" in self.config.name:
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"data_dir": base_dir,
"split": "train",
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={"data_dir": base_dir, "split": "test"},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={
"data_dir": base_dir,
"split": "dev",
},
),
]
else:
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"data_dir": base_dir,
"split": "train",
},
),
]
def _generate_examples(self, data_dir, split):
"""Yields examples."""
if "dialogues" in self.config.name:
if "all" in self.config.name:
file_dict = {
domain: os.path.join(os.path.join(data_dir, domain), split + ".json") for domain in _DOMAINS
}
else:
domain = self.config.name.split("_")[0]
file_dict = {domain: os.path.join(os.path.join(data_dir, domain), split + ".json")}
id_ = -1
for domain, filepath in file_dict.items():
with open(filepath, encoding="utf-8") as f:
conversations = json.load(f)
for conversation in conversations:
id_ += 1
conversation["domain"] = domain
for turn in conversation["messages"]:
if "attrs" in turn:
attrnames = [kb_triplet.get("attrname", "") for kb_triplet in turn["attrs"]]
attrvalues = [kb_triplet.get("attrvalue", "") for kb_triplet in turn["attrs"]]
names = [kb_triplet.get("name", "") for kb_triplet in turn["attrs"]]
else:
attrnames, attrvalues, names = [], [], []
turn["attrs"] = {"attrname": attrnames, "attrvalue": attrvalues, "name": names}
yield id_, conversation
else:
if "all" in self.config.name:
file_dict = {
domain: os.path.join(os.path.join(data_dir, domain), "kb_" + domain + ".json")
for domain in _DOMAINS
}
else:
domain = self.config.name.split("_")[0]
file_dict = {domain: os.path.join(os.path.join(data_dir, domain), "kb_" + domain + ".json")}
id_ = -1
for domain, filepath in file_dict.items():
with open(filepath, encoding="utf-8") as f:
kb_dict = json.load(f)
for head_entity, kb_triplets in kb_dict.items():
id_ += 1
yield id_, {"head_entity": head_entity, "kb_triplets": kb_triplets, "domain": domain}
|