Upload 4 files

clef24_dataset_es.py

@@ -0,0 +1,80 @@
+"""Multilang Dataset loading script."""
+
+from datasets import DatasetInfo, BuilderConfig, Version, GeneratorBasedBuilder, DownloadManager
+from datasets import SplitGenerator, Split, Features, Value
+from typing import Generator, Tuple, Union
+
+import os
+
+_DESCRIPTION = """
+This dataset includes Spanish Twitter data for CLEF 2024 CheckThat! Lab task1.
+"""
+
+_CITATION = """\
+@inproceedings{barron2024clef,
+  title={The CLEF-2024 CheckThat! Lab: Check-Worthiness, Subjectivity, Persuasion, Roles, Authorities, and Adversarial Robustness},
+  author={Barr{\'o}n-Cede{\~n}o, Alberto and Alam, Firoj and Chakraborty, Tanmoy and Elsayed, Tamer and Nakov, Preslav and Przyby{\l}a, Piotr and Stru{\ss}, Julia Maria and Haouari, Fatima and Hasanain, Maram and Ruggeri, Federico and others},
+  booktitle={European Conference on Information Retrieval},
+  pages={449--458},
+  year={2024},
+  organization={Springer}
+}
+"""
+
+_LICENSE = "Your dataset's license here."
+
+class CLEF24EsData(GeneratorBasedBuilder):
+    """A multilingual text dataset."""
+
+    BUILDER_CONFIGS = [
+        BuilderConfig(name="clef24_es_tweet_data", version=Version("1.0.0"), description="Multilingual dataset for text classification."),
+    ]
+
+    DEFAULT_CONFIG_NAME = "clef24_es_tweet_data"  # Default configuration name.
+
+    def _info(self):
+        """Construct the DatasetInfo object."""
+        return DatasetInfo(
+            description=_DESCRIPTION,
+            features=Features({
+                "tweet_id": Value("string"),
+                "tweet_url": Value("string"),
+                "tweet_text": Value("string"),
+                "class_label": Value("string"),
+            }),
+            supervised_keys=("Text", "class_label"),
+            homepage="https://gitlab.com/checkthat_lab/clef2024-checkthat-lab/-/tree/main/task1",
+            citation=_CITATION,
+            license=_LICENSE,
+        )
+
+    def _split_generators(self, dl_manager: DownloadManager) -> list[SplitGenerator]:
+        """Returns SplitGenerators."""
+        # Assumes your dataset is located in "."
+        data_dir = os.path.abspath(".")
+        splits = {"train": Split.TRAIN, "dev": Split.VALIDATION, "test": Split.TEST}
+        
+        return [
+            SplitGenerator(
+                name=splits[split],
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, f"{split}.tsv"),
+                    "split": splits[split]
+                },
+            )
+            for split in splits.keys()
+        ]
+
+    def _generate_examples(self, filepath: Union[str, os.PathLike], split: str) -> Generator[Tuple[str, dict], None, None]:
+        """Yields examples."""
+        with open(filepath, encoding="utf-8") as f:
+            for id_, row in enumerate(f):
+                if id_ == 0:  # Optionally skip header
+                    continue
+                cols = row.strip().split('\t')
+                yield f"{split}_{id_}", {
+                    "tweet_id": cols[0],
+                    "tweet_url": cols[1],
+                    "sentence": cols[2],
+                    "label": cols[3],
+                }