Create dataset.py

dataset.py

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+import datasets
+
+_CITATION = """\
+@misc{yoruba2025numericalqa,
+  title     = {Yorùbá Numerical and Logical Reasoning QA Dataset},
+  author    = {Fiyinfoluwa Oyesanmi and Peter Olukanmi},
+  year      = {2025},
+  url       = {https://huggingface.co/datasets/fiyinoye/yoruba-arithmetic-dataset},
+  note      = {A dataset for evaluating reasoning and numeral understanding in Yorùbá.}
+}
+"""
+
+_DESCRIPTION = """\
+This dataset contains three subsets of question-answer pairs written in Yorùbá:
+(1) Arithmetic reasoning, (2) Calendar/time reasoning, and (3) Traditional numeral interpretation.
+It is intended for evaluating LLMs' reasoning in low-resource, indigenous languages.
+"""
+
+_HOMEPAGE = "https://huggingface.co/datasets/fiyinoye/yoruba-arithmetic-dataset"
+_LICENSE = "CC-BY-4.0"
+
+_URLS = {
+    "arithmetic": "https://huggingface.co/datasets/fiyinoye/yoruba-arithmetic-dataset/blob/main/data/arithmetic.json",
+    "calendar": "https://huggingface.co/datasets/fiyinoye/yoruba-arithmetic-dataset/blob/main/data/calendar.json",
+    "numerals": "https://huggingface.co/datasets/fiyinoye/yoruba-arithmetic-dataset/blob/main/data/numerals.json",
+}
+
+class YorubaNumericalReasoning(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.0.0")
+    
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features({
+                "id": datasets.Value("string"),
+                "subset": datasets.ClassLabel(names=["arithmetic", "calendar", "numerals"]),
+                "question": datasets.Value("string")
+            }),
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+            license=_LICENSE,
+        )
+
+    def _split_generators(self, dl_manager):
+        downloaded = dl_manager.download_and_extract(_URLS)
+        return [
+            datasets.SplitGenerator(
+                name="arithmetic", gen_kwargs={"filepath": downloaded["arithmetic"], "subset": "arithmetic"}
+            ),
+            datasets.SplitGenerator(
+                name="calendar", gen_kwargs={"filepath": downloaded["calendar"], "subset": "calendar"}
+            ),
+            datasets.SplitGenerator(
+                name="numerals", gen_kwargs={"filepath": downloaded["numerals"], "subset": "numerals"}
+            ),
+        ]
+
+    def _generate_examples(self, filepath, category):
+        import json
+        with open(filepath, encoding="utf-8") as f:
+            data = json.load(f)
+            for i, row in enumerate(data):
+                yield i, {
+                    "id": row.get("id", str(i)),
+                    "subset": subset,
+                    "question": row["question"]
+                }