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# 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.
"""DSTC11 Dataset."""
import json
import datasets
_CITATION = """\
@misc{gung2023natcs,
title={NatCS: Eliciting Natural Customer Support Dialogues},
author={James Gung and Emily Moeng and Wesley Rose and Arshit Gupta and Yi Zhang and Saab Mansour},
year={2023},
eprint={2305.03007},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
@misc{gung2023intent,
title={Intent Induction from Conversations for Task-Oriented Dialogue Track at DSTC 11},
author={James Gung and Raphael Shu and Emily Moeng and Wesley Rose and Salvatore Romeo and Yassine Benajiba and Arshit Gupta and Saab Mansour and Yi Zhang},
year={2023},
eprint={2304.12982},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
"""
_DESCRIPTION = """
This repository contains data, relevant scripts and baseline code for the Dialog Systems Technology Challenge (DSTC11).
"""
_HOMEPAGE = "https://github.com/amazon-science/dstc11-track2-intent-induction"
_URLs = {
"validation": "development/dialogues.jsonl.gz",
"test-banking": "test-banking/dialogues.jsonl.gz",
"test-finance": "test-finance/dialogues.jsonl.gz",
}
class Dstc11(datasets.GeneratorBasedBuilder):
"""Data from the DSTC 11 tasks."""
VERSION = datasets.Version("1.0.0")
BUILDER_CONFIGS = [
datasets.BuilderConfig(
name="data",
version=datasets.Version("1.0.0"),
description=_DESCRIPTION,
),
datasets.BuilderConfig(name="docs", version=datasets.Version("1.0.0"), description=_DESCRIPTION),
]
DEFAULT_CONFIG_NAME = "data"
def _info(self):
features=datasets.Features({
"dialogue_id": datasets.Value("string"),
"turns": datasets.Sequence(
datasets.Features({
"turn_id": datasets.Value("string"),
"speaker_role": datasets.Value("string"),
"utterance": datasets.Value("string"),
"dialogue_acts": datasets.Sequence(
datasets.Value("string")
),
"intents": datasets.Sequence(
datasets.Value("string")
),
})
)
})
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
supervised_keys=None,
citation=_CITATION,
homepage=_HOMEPAGE)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
data_dir = dl_manager.download_and_extract(_URLs)
return [
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={"filepaths": [data_dir["validation"]], "split": "validation"},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={"filepaths": [data_dir["test-banking"], data_dir["test-finance"]], "split": "test"},
),
datasets.SplitGenerator(
name="test.banking",
gen_kwargs={"filepaths": [data_dir["test-banking"]], "split": "test.banking"},
),
datasets.SplitGenerator(
name="test.finance",
gen_kwargs={"filepaths": [data_dir["test-finance"]], "split": "test.finance"},
),
]
def _generate_examples(self, filepaths, split):
key = 0
for filepath in filepaths:
for line in open(filepath, encoding="utf-8"):
line = json.loads(line)
yield key, line
key += 1
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