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import json
from pathlib import Path
from typing import Dict, List, Tuple
import datasets
from seacrowd.utils.configs import SEACrowdConfig
from seacrowd.utils.constants import Tasks
_CITATION = """\
@article{majewska2022cross,
title={Cross-lingual dialogue dataset creation via outline-based generation},
author={Majewska, Olga and Razumovskaia, Evgeniia and Ponti, Edoardo Maria and Vuli{\'c}, Ivan and Korhonen, Anna},
journal={arXiv preprint arXiv:2201.13405},
year={2022}
}
"""
_LANGUAGES = ["ind"]
_LOCAL = False
_DATASETNAME = "cod"
_DESCRIPTION = """\
Cross-lingual Outline-based Dialogue (COD) is a dataset comprised of manually generated, localized, and cross-lingually aligned Task-Oriented-Dialogue (TOD) data that served as the source of dialogue prompts.
COD enables natural language understanding, dialogue state tracking, and end-to-end dialogue modeling and evaluation.
Majewska et al. (2022) create COD using a novel outline-based annotation pipeline for multilingual TOD by Majewska et al. (2022).
English Schema-Guided Dialogue (SGD; Shah et al., 2018; Rastogi et al., 2020) dataset is automatically sampled and mapped into outlines. The outlines are then paraphrased and adapted to the local target domain by human subjects.
"""
_HOMEPAGE = "https://github.com/cambridgeltl/COD"
_LICENSE = "Unknown"
_URLS = {
_DATASETNAME: {
"validation": "https://raw.githubusercontent.com/cambridgeltl/COD/main/id_dev.json",
"test": "https://raw.githubusercontent.com/cambridgeltl/COD/main/id_test.json",
},
}
_SUPPORTED_TASKS = [Tasks.DIALOGUE_SYSTEM]
_SOURCE_VERSION = "1.0.0"
_SEACROWD_VERSION = "2024.06.20"
class NewDataset(datasets.GeneratorBasedBuilder):
"""Cross-lingual Outline-based Dialogue (COD) is a dataset comprises manually generated, localised, and cross-lingually aligned Task-Oriented-Dialogue (TOD) data which served as the source of dialogue prompts."""
SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
SEACROWD_VERSION = datasets.Version(_SEACROWD_VERSION)
BUILDER_CONFIGS = [
SEACrowdConfig(
name="cod_source",
version=SOURCE_VERSION,
description="Cross-lingual Outline-based Dialogue (COD) source schema",
schema="source",
subset_id="cod",
),
]
DEFAULT_CONFIG_NAME = "cod_source"
def _info(self) -> datasets.DatasetInfo:
if self.config.schema == "source":
features = datasets.Features(
{
"index": datasets.Value("string"),
"dialogue_id": datasets.Value("string"),
"services": [datasets.Value("string")],
"turns": [
{
"speaker": datasets.Value("string"),
"utterance": datasets.Value("string"),
"frames": [
{
"actions": [
{
"act": datasets.Value("string"),
"slot": datasets.Value("string"),
"values": [datasets.Value("string")],
}
],
"service": datasets.Value("string"),
"slots": [
{
"exclusive_end": datasets.Value("int32"),
"slot": datasets.Value("string"),
"start": datasets.Value("int32"),
}
],
"state": {
"active_intent": datasets.Value("string"),
"requested_slots": [datasets.Value("string")],
"slot_values": [
{"slot": datasets.Value("string"), "values": [datasets.Value("string")]},
],
},
}
],
}
],
}
)
else:
raise NotImplementedError()
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
urls = _URLS[_DATASETNAME]
data_dir = dl_manager.download_and_extract(urls)
return [
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"filepath": data_dir["test"],
"split": "test",
},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={
"filepath": data_dir["validation"],
"split": "dev",
},
),
]
def _generate_examples(self, filepath: Path, split: str) -> Tuple[int, Dict]:
with open(filepath, "r+") as fw:
data = json.loads(fw.read())
if self.config.schema == "source":
for idx, example in enumerate(data):
example["index"] = str(idx)
for turn in example["turns"]:
for frame in turn["frames"]:
if "state" not in frame:
continue
ls_slot_values = []
for slot in frame["state"]["slot_values"]:
ls_slot_values.append({"slot": slot, "values": frame["state"]["slot_values"][slot]})
frame["state"]["slot_values"] = ls_slot_values
yield str(idx), example
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