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id_stance.py

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+import json
+from pathlib import Path
+from typing import List
+
+import datasets
+import pandas as pd
+
+from nusacrowd.utils import schemas
+from nusacrowd.utils.configs import NusantaraConfig
+from nusacrowd.utils.constants import Tasks
+
+_CITATION = """\
+@INPROCEEDINGS{8629144,  
+  author={R. {Jannati} and R. {Mahendra} and C. W. {Wardhana} and M. {Adriani}},
+  booktitle={2018 International Conference on Asian Language Processing (IALP)},
+  title={Stance Classification Towards Political Figures on Blog Writing},
+  year={2018},
+  volume={},
+  number={},
+  pages={96-101},
+}
+"""
+
+_LANGUAGES = ["ind"]  # We follow ISO639-3 language code (https://iso639-3.sil.org/code_tables/639/data)
+_LOCAL = False
+
+_DATASETNAME = "id_stance"
+_DESCRIPTION = """\
+Stance Classification Towards Political Figures on Blog Writing.
+This dataset contains dataset from the second research, which is combined from the first research and new dataset.
+The dataset consist of 337 data, about five target and every target have 1 different event.
+Two label are used: 'For' and 'Againts'.
+1. For - the text that is created by author is support the target in an event
+2. Against - the text that is created by author is oppose the target in an event
+"""
+_HOMEPAGE = "https://github.com/reneje/id_stance_dataset_article-Stance-Classification-Towards-Political-Figures-on-Blog-Writing"
+_LICENSE = "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License"
+_URLs = {
+    _DATASETNAME: "https://raw.githubusercontent.com/reneje/id_stance_dataset_article-Stance-Classification-Towards-Political-Figures-on-Blog-Writing/master/dataset_stance_2_label_2018_building_by_rini.csv"
+}
+_SUPPORTED_TASKS = [Tasks.TEXTUAL_ENTAILMENT]
+_SOURCE_VERSION = "1.0.0"
+_NUSANTARA_VERSION = "1.0.0"
+
+
+def parse_list(content):
+    if (not content):
+        return []
+    try:
+        return json.loads(content)
+    except:
+        return json.loads("[\"" + content[1:-1].replace("\"", "\\\"") + "\"]")
+
+
+class IdStance(datasets.GeneratorBasedBuilder):
+    """The ID Stance dataset is annotated with a label whether the article is in favor of the person in the context of the event"""
+
+    BUILDER_CONFIGS = [
+        NusantaraConfig(
+            name="id_stance_source",
+            version=datasets.Version(_SOURCE_VERSION),
+            description="IdStance source schema",
+            schema="source",
+            subset_id="id_stance",
+        ),
+        NusantaraConfig(
+            name="id_stance_nusantara_pairs",
+            version=datasets.Version(_NUSANTARA_VERSION),
+            description="IdStance Nusantara schema",
+            schema="nusantara_pairs",
+            subset_id="id_stance",
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = "id_stance_source"
+
+    def _info(self):
+        if self.config.schema == "source":
+            features = datasets.Features(
+                {
+                    "person": datasets.Value("string"),
+                    "event": datasets.Value("string"),
+                    "title": datasets.Value("string"),
+                    "content": datasets.Value("string"),
+                    "stance_final": datasets.Value("string"),
+                }
+            )
+        elif self.config.schema == "nusantara_pairs":
+            features = schemas.pairs_features(["for", "against", "no"])
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
+        data_path = Path(dl_manager.download_and_extract(_URLs[_DATASETNAME]))
+        data_files = {
+            "train": data_path,
+        }
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"filepath": data_files["train"]},
+            ),
+        ]
+
+    def _generate_examples(self, filepath: Path):
+        df = pd.read_csv(filepath, sep=";", header="infer", keep_default_na=False).reset_index()
+        df.columns = ["id", "person", "event", "title", "content", "stance_final", ""]
+        df.content = df.content.apply(parse_list)
+
+        if self.config.schema == "source":
+            for row in df.itertuples():
+                ex = {
+                    "person": row.person,
+                    "event": row.event,
+                    "title": row.title,
+                    "content": " ".join(row.content),
+                    "stance_final": row.stance_final
+                }
+                yield row.id, ex
+        elif self.config.schema == "nusantara_pairs":
+            for row in df.itertuples():
+                ex = {
+                    "id": row.id,
+                    "text_1": row.person + " | " + row.event,
+                    "text_2": " ".join([row.title] + row.content),
+                    "label": 'against' if row.stance_final == 'againts' else row.stance_final
+                }
+                yield row.id, ex
+        else:
+            raise ValueError(f"Invalid config: {self.config.name}")