# 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