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x_fact.py

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+from pathlib import Path
+from typing import Dict, List, Tuple
+
+import datasets
+
+from nusacrowd.nusa_datasets.x_fact.utils.x_fact_utils import \
+    load_x_fact_dataset
+from nusacrowd.utils.configs import NusantaraConfig
+from nusacrowd.utils.constants import Tasks
+
+_CITATION = """\
+@inproceedings{gupta2021xfact,
+      title={{X-FACT: A New Benchmark Dataset for Multilingual Fact Checking}},
+      author={Gupta, Ashim and Srikumar, Vivek},
+      booktitle = "Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics",
+      month = jul,
+      year = "2021",
+      address = "Online",
+      publisher = "Association for Computational Linguistics",
+}
+"""
+_DATASETNAME = "x_fact"
+
+_DESCRIPTION = """\
+X-FACT: the largest publicly available multilingual dataset for factual verification of naturally existing realworld claims.
+"""
+
+_HOMEPAGE = "https://github.com/utahnlp/x-fact"
+
+_LANGUAGES = [
+    'ara', 'aze', 'ben', 'deu', 'spa', 
+    'fas', 'fra', 'guj', 'hin', 'ind', 
+    'ita', 'kat', 'mar', 'nor', 'nld', 
+    'pan', 'pol', 'por', 'ron', 'rus',
+    'sin', 'srp', 'sqi', 'tam', 'tur'
+]
+_LOCAL = False
+
+_LICENSE = "MIT"
+
+_URLS = {
+    "train": "https://raw.githubusercontent.com/utahnlp/x-fact/main/data/x-fact-including-en/train.all.tsv",
+    "validation": "https://raw.githubusercontent.com/utahnlp/x-fact/main/data/x-fact-including-en/dev.all.tsv",
+    "test": {
+        "in_domain": "https://raw.githubusercontent.com/utahnlp/x-fact/main/data/x-fact-including-en/test.all.tsv",
+        "out_domain": "https://raw.githubusercontent.com/utahnlp/x-fact/main/data/x-fact-including-en/ood.tsv",
+    },
+}
+
+_SUPPORTED_TASKS = [Tasks.FACT_CHECKING]
+
+_SOURCE_VERSION = "1.0.0"
+
+_NUSANTARA_VERSION = "1.0.0"
+
+
+class XFact(datasets.GeneratorBasedBuilder):
+    """X-FACT: the largest publicly available multilingual dataset for factual verification of naturally existing realworld claims."""
+
+    SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
+    NUSANTARA_VERSION = datasets.Version(_NUSANTARA_VERSION)
+
+    BUILDER_CONFIGS = [
+        NusantaraConfig(
+            name="x_fact_source",
+            version=SOURCE_VERSION,
+            description="x_fact source schema",
+            schema="source",
+            subset_id="x_fact",
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = "x_fact_source"
+
+    def _info(self) -> datasets.DatasetInfo:
+
+        if self.config.schema == "source":
+            features = datasets.Features(
+                {
+                    "language": datasets.Value("string"),
+                    "site": datasets.Value("string"),
+                    "evidence_1": datasets.Value("string"),
+                    "evidence_2": datasets.Value("string"),
+                    "evidence_3": datasets.Value("string"),
+                    "evidence_4": datasets.Value("string"),
+                    "evidence_5": datasets.Value("string"),
+                    "link_1": datasets.Value("string"),
+                    "link_2": datasets.Value("string"),
+                    "link_3": datasets.Value("string"),
+                    "link_4": datasets.Value("string"),
+                    "link_5": datasets.Value("string"),
+                    "claimDate": datasets.Value("string"),
+                    "reviewDate": datasets.Value("string"),
+                    "claimant": datasets.Value("string"),
+                    "claim": datasets.Value("string"),
+                    "label": datasets.Value("string"),
+                }
+            )
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": _URLS["train"],
+                    "split": "train",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "filepath": _URLS["validation"],
+                    "split": "dev",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.splits.NamedSplit("TEST_IN_DOMAIN"),
+                gen_kwargs={
+                    "filepath": _URLS["test"]["in_domain"],
+                    "split": "test_in_domain",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.splits.NamedSplit("TEST_OUT_DOMAIN"),
+                gen_kwargs={
+                    "filepath": _URLS["test"]["out_domain"],
+                    "split": "test_out_domain",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath: Path, split: str) -> Tuple[int, Dict]:
+
+        df = load_x_fact_dataset(filepath)
+        if self.config.schema == "source":
+            for row in df.itertuples():
+                entry = {
+                    "language": row.language,
+                    "site": row.site,
+                    "evidence_1": row.evidence_1,
+                    "evidence_2": row.evidence_2,
+                    "evidence_3": row.evidence_3,
+                    "evidence_4": row.evidence_4,
+                    "evidence_5": row.evidence_5,
+                    "link_1": row.link_1,
+                    "link_2": row.link_2,
+                    "link_3": row.link_3,
+                    "link_4": row.link_4,
+                    "link_5": row.link_5,
+                    "claimDate": row.claimDate,
+                    "reviewDate": row.reviewDate,
+                    "claimant": row.claimant,
+                    "claim": row.claim,
+                    "label": row.label,
+                }
+                yield row.index, entry