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nusax_senti.py

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+from pathlib import Path
+from typing import Dict, List, Tuple
+
+import datasets
+import pandas as pd
+
+from nusacrowd.utils import schemas
+from nusacrowd.utils.configs import NusantaraConfig
+from nusacrowd.utils.constants import (DEFAULT_NUSANTARA_VIEW_NAME,
+                                       DEFAULT_SOURCE_VIEW_NAME, Tasks)
+
+_LOCAL = False
+
+_DATASETNAME = "nusax_senti"
+_SOURCE_VIEW_NAME = DEFAULT_SOURCE_VIEW_NAME
+_UNIFIED_VIEW_NAME = DEFAULT_NUSANTARA_VIEW_NAME
+
+_LANGUAGES = ["ind", "ace", "ban", "bjn", "bbc", "bug", "jav", "mad", "min", "nij", "sun", "eng"]  # We follow ISO639-3 language code (https://iso639-3.sil.org/code_tables/639/data)
+
+_CITATION = """\
+@misc{winata2022nusax,
+      title={NusaX: Multilingual Parallel Sentiment Dataset for 10 Indonesian Local Languages},
+      author={Winata, Genta Indra and Aji, Alham Fikri and Cahyawijaya,
+      Samuel and Mahendra, Rahmad and Koto, Fajri and Romadhony,
+      Ade and Kurniawan, Kemal and Moeljadi, David and Prasojo,
+      Radityo Eko and Fung, Pascale and Baldwin, Timothy and Lau,
+      Jey Han and Sennrich, Rico and Ruder, Sebastian},
+      year={2022},
+      eprint={2205.15960},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+"""
+
+_DESCRIPTION = """\
+NusaX is a high-quality multilingual parallel corpus that covers 12 languages, Indonesian, English, and 10 Indonesian local languages, namely Acehnese, Balinese, Banjarese, Buginese, Madurese, Minangkabau, Javanese, Ngaju, Sundanese, and Toba Batak.
+
+NusaX-Senti is a 3-labels (positive, neutral, negative) sentiment analysis dataset for 10 Indonesian local languages + Indonesian and English.
+"""
+
+_HOMEPAGE = "https://github.com/IndoNLP/nusax/tree/main/datasets/sentiment"
+
+_LICENSE = "Creative Commons Attribution Share-Alike 4.0 International"
+
+_SUPPORTED_TASKS = [Tasks.SENTIMENT_ANALYSIS]
+
+_SOURCE_VERSION = "1.0.0"
+
+_NUSANTARA_VERSION = "1.0.0"
+
+_URLS = {
+    "train": "https://raw.githubusercontent.com/IndoNLP/nusax/main/datasets/sentiment/{lang}/train.csv",
+    "validation": "https://raw.githubusercontent.com/IndoNLP/nusax/main/datasets/sentiment/{lang}/valid.csv",
+    "test": "https://raw.githubusercontent.com/IndoNLP/nusax/main/datasets/sentiment/{lang}/test.csv",
+}
+
+
+def nusantara_config_constructor(lang, schema, version):
+    """Construct NusantaraConfig with nusax_senti_{lang}_{schema} as the name format"""
+    if schema != "source" and schema != "nusantara_text":
+        raise ValueError(f"Invalid schema: {schema}")
+
+    if lang == "":
+        return NusantaraConfig(
+            name="nusax_senti_{schema}".format(schema=schema),
+            version=datasets.Version(version),
+            description="nusax_senti with {schema} schema for all 12 languages".format(schema=schema),
+            schema=schema,
+            subset_id="nusax_senti",
+        )
+    else:
+        return NusantaraConfig(
+            name="nusax_senti_{lang}_{schema}".format(lang=lang, schema=schema),
+            version=datasets.Version(version),
+            description="nusax_senti with {schema} schema for {lang} language".format(lang=lang, schema=schema),
+            schema=schema,
+            subset_id="nusax_senti",
+        )
+
+
+LANGUAGES_MAP = {
+    "ace": "acehnese",
+    "ban": "balinese",
+    "bjn": "banjarese",
+    "bug": "buginese",
+    "eng": "english",
+    "ind": "indonesian",
+    "jav": "javanese",
+    "mad": "madurese",
+    "min": "minangkabau",
+    "nij": "ngaju",
+    "sun": "sundanese",
+    "bbc": "toba_batak",
+}
+
+
+class NusaXSenti(datasets.GeneratorBasedBuilder):
+    """NusaX-Senti is a 3-labels (positive, neutral, negative) sentiment analysis dataset for 10 Indonesian local languages + Indonesian and English."""
+
+    BUILDER_CONFIGS = (
+        [nusantara_config_constructor(lang, "source", _SOURCE_VERSION) for lang in LANGUAGES_MAP]
+        + [nusantara_config_constructor(lang, "nusantara_text", _NUSANTARA_VERSION) for lang in LANGUAGES_MAP]
+        + [nusantara_config_constructor("", "source", _SOURCE_VERSION), nusantara_config_constructor("", "nusantara_text", _NUSANTARA_VERSION)]
+    )
+
+    DEFAULT_CONFIG_NAME = "nusax_senti_ind_source"
+
+    def _info(self) -> datasets.DatasetInfo:
+        if self.config.schema == "source":
+            features = datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "text": datasets.Value("string"),
+                    "label": datasets.Value("string"),
+                }
+            )
+        elif self.config.schema == "nusantara_text":
+            features = schemas.text_features(["negative", "neutral", "positive"])
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
+        """Returns SplitGenerators."""
+        if self.config.name == "nusax_senti_source" or self.config.name == "nusax_senti_nusantara_text":
+            # Load all 12 languages
+            train_csv_path = dl_manager.download_and_extract([_URLS["train"].format(lang=LANGUAGES_MAP[lang]) for lang in LANGUAGES_MAP])
+            validation_csv_path = dl_manager.download_and_extract([_URLS["validation"].format(lang=LANGUAGES_MAP[lang]) for lang in LANGUAGES_MAP])
+            test_csv_path = dl_manager.download_and_extract([_URLS["test"].format(lang=LANGUAGES_MAP[lang]) for lang in LANGUAGES_MAP])
+        else:
+            lang = self.config.name[12:15]
+            train_csv_path = Path(dl_manager.download_and_extract(_URLS["train"].format(lang=LANGUAGES_MAP[lang])))
+            validation_csv_path = Path(dl_manager.download_and_extract(_URLS["validation"].format(lang=LANGUAGES_MAP[lang])))
+            test_csv_path = Path(dl_manager.download_and_extract(_URLS["test"].format(lang=LANGUAGES_MAP[lang])))
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"filepath": train_csv_path},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"filepath": validation_csv_path},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"filepath": test_csv_path},
+            ),
+        ]
+
+    def _generate_examples(self, filepath: Path) -> Tuple[int, Dict]:
+        if self.config.schema != "source" and self.config.schema != "nusantara_text":
+            raise ValueError(f"Invalid config: {self.config.name}")
+
+        if self.config.name == "nusax_senti_source" or self.config.name == "nusax_senti_nusantara_text":
+            ldf = []
+            for fp in filepath:
+                ldf.append(pd.read_csv(fp))
+            df = pd.concat(ldf, axis=0, ignore_index=True).reset_index()
+            # Have to use index instead of id to avoid duplicated key
+            df = df.drop(columns=["id"]).rename(columns={"index": "id"})
+        else:
+            df = pd.read_csv(filepath).reset_index()
+
+        for row in df.itertuples():
+            ex = {"id": str(row.id), "text": row.text, "label": row.label}
+            yield row.id, ex