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