Add files using upload-large-folder tool

dataset.py

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+import os
+
+from datasets import DatasetInfo, GeneratorBasedBuilder, SplitGenerator, Split, Features, Value
+
+
+class WikiTableQuestions(GeneratorBasedBuilder):
+    """
+    A simple Hugging Face dataset builder for evaluating question-answering (QA)
+    over tabular data, using file paths as context (CSV, HTML, TSV).
+
+    The dataset is loaded from a JSON file containing QA samples and context file paths.
+    """
+
+    def _info(self):
+        """
+        Returns the metadata and schema of the dataset.
+
+        Returns:
+            DatasetInfo: Contains description, features (schema), and supervised keys.
+        """
+        return DatasetInfo(
+            description="QA over tabular data with file paths as context",
+            features=Features({
+                "id": Value("string"),
+                "utterance": Value("string"),
+                "target_value": Value("string"),
+                "context": Features({
+                    "csv": Value("string"),
+                    "html": Value("string"),
+                    "tsv": Value("string"),
+                }),
+            }),
+            supervised_keys=None,
+        )
+
+    def _split_generators(self, dl_manager):
+        """
+        Downloads and defines dataset splits.
+
+        Args:
+            dl_manager (DownloadManager): The Hugging Face datasets download manager.
+
+        Returns:
+            List[SplitGenerator]: A list containing a single test split generator.
+        """
+        downloaded_files = dl_manager.download({
+            "train": "examples/examples-train.json",
+            "test": "examples/examples-test.json"
+        })
+        return [
+            SplitGenerator(name=Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
+            SplitGenerator(name=Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
+        ]
+
+    def _generate_examples(self, filepath):
+        """
+        Yields examples from the dataset JSON file.
+
+        Each example consists of a question, target value, and paths to context files
+        (CSV, HTML, TSV). The relative paths are resolved into absolute paths based
+        on the JSON file's directory.
+
+        Args:
+            filepath (str): Path to the JSON file containing dataset examples.
+
+        Yields:
+            Tuple[int, dict]: A tuple of the index and the data sample dictionary.
+        """
+        import json
+        with open(filepath, encoding="utf-8") as f:
+            data = json.load(f)
+
+        for i, item in enumerate(data):
+            yield i, {
+                "id": item["id"],
+                "utterance": item["utterance"],
+                "target_value": item["target_value"],
+                "context": {
+                    "csv": item["context"]["csv"],
+                    "html": item["context"]["html"],
+                    "tsv": item["context"]["tsv"],
+                },
+            }