Create afriqa-gold-passages.py

afriqa-gold-passages.py

@@ -0,0 +1,114 @@
+"""AfriQA GOLD Passages dataset."""
+
+
+import json
+import os
+from textwrap import dedent
+
+import datasets
+
+
+_HOMEPAGE = "https://github.com/masakhane-io/afriqa"
+
+_DESCRIPTION = """\
+AfriQA: Cross-lingual Open-Retrieval Question Answering for African Languages
+AfriQA is the first cross-lingual question-answering (QA) dataset with a focus on African languages. 
+The dataset includes over 12,000 XOR QA examples across 10 African languages, making it an invaluable resource for developing more equitable QA technology.
+"""
+
+_CITATION = """\
+"""
+
+_URL = "https://github.com/masakhane-io/afriqa/raw/main/gold_passages/queries/"
+
+_LANG_2_PIVOT = {
+    "bem": "en",
+    "fon": "fr",
+    "hau": "en",
+    "ibo": "en",
+    "kin": "en",
+    "swa": "en",
+    "twi": "en",
+    "wol": "fr",
+    "yor": "en",
+    "zul": "en",
+}
+
+class AfriQAConfig(datasets.BuilderConfig):
+    """BuilderConfig for AfriQA"""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig for AfriQA.
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(AfriQAConfig, self).__init__(**kwargs)
+
+
+class AfriQA(datasets.GeneratorBasedBuilder):
+    """AfriQA dataset."""
+
+    VERSION = datasets.Version("1.0.0")
+
+    BUILDER_CONFIGS = [
+        AfriQAConfig(name="bem", version=datasets.Version("1.0.0"), description="AfriQA Gold Passages Bemba dataset"),
+        AfriQAConfig(name="fon", version=datasets.Version("1.0.0"), description="AfriQA Gold Passages Fon dataset"),
+        AfriQAConfig(name="hau", version=datasets.Version("1.0.0"), description="AfriQA Gold Passages Hausa dataset"),
+        AfriQAConfig(name="ibo", version=datasets.Version("1.0.0"), description="AfriQA Gold Passages Igbo dataset"),
+        AfriQAConfig(name="kin", version=datasets.Version("1.0.0"), description="AfriQA Gold Passages Kinyarwanda dataset"),
+        AfriQAConfig(name="swa", version=datasets.Version("1.0.0"), description="AfriQA Gold Passages Swahili dataset"),
+        AfriQAConfig(name="twi", version=datasets.Version("1.0.0"), description="AfriQA Gold Passages Twi dataset"),
+        AfriQAConfig(name="wol", version=datasets.Version("1.0.0"), description="AfriQA Gold Passages Wolof dataset"),
+        AfriQAConfig(name="yor", version=datasets.Version("1.0.0"), description="AfriQA Gold Passages Yoruba dataset"),
+        AfriQAConfig(name="zul", version=datasets.Version("1.0.0"), description="AfriQA Gold Passages Zulu dataset"),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "question_lang": datasets.Value("string"),
+                    "question_translated": datasets.Value("string"),
+                    "context": datasets.Value("string"),
+                    "title": datasets.Value("string"),
+                    "answer_pivot": datasets.Value("string"),
+                    "answer_start": datasets.Value("string"),
+                    "answer_lang": datasets.Value("string"),
+                }
+            ),
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        urls_to_download = {
+            "train": f"{_URL}{self.config.name}/gold_span_passages.afriqa.{self.config.name}.{_LANG_2_PIVOT[self.config.name]}.train.json",
+            "dev": f"{_URL}{self.config.name}/gold_span_passages.afriqa.{self.config.name}.{_LANG_2_PIVOT[self.config.name]}.dev.json",
+            "test": f"{_URL}{self.config.name}/gold_span_passages.afriqa.{self.config.name}.{_LANG_2_PIVOT[self.config.name]}.test.json",
+        }
+        downloaded_files = dl_manager.download_and_extract(urls_to_download)
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
+        ]
+
+    def _generate_examples(self, filepath):
+        """Yields examples."""
+        with open(filepath, encoding="utf-8-sig") as f:
+            for _, row in enumerate(f):
+                example = json.loads(row)
+                _id = example["id"]
+
+                yield _id, {
+                    "question_lang": example["question_lang"],
+                    "question_translated": example["question_translated"],
+                    "context": example["context"],
+                    "title": example["title"],
+                    "answer_pivot": example["answer_pivot"]["text"][0],
+                    "answer_start": example["answer_pivot"]["answer_start"][0],
+                    "answer_lang": example["answer_lang"],
+                }