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