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cod.py

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+import json
+from pathlib import Path
+from typing import Dict, List, Tuple
+
+import datasets
+
+from nusacrowd.utils.configs import NusantaraConfig
+from nusacrowd.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"
+
+_NUSANTARA_VERSION = "1.0.0"
+
+
+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)
+    NUSANTARA_VERSION = datasets.Version(_NUSANTARA_VERSION)
+
+    BUILDER_CONFIGS = [
+        NusantaraConfig(
+            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