danfever metadata and reader

danfever.py

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+# coding=utf-8
+# Copyright 2020 HuggingFace Datasets Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# Lint as: python3
+"""DanFEVER: A FEVER dataset for Danish"""
+
+import csv
+import os
+
+import datasets
+
+
+logger = datasets.logging.get_logger(__name__)
+
+
+_CITATION = """\
+@inproceedings{norregaard-derczynski-2021-danfever,
+    title = "{D}an{FEVER}: claim verification dataset for {D}anish",
+    author = "N{\o}rregaard, Jeppe  and
+      Derczynski, Leon",
+    booktitle = "Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa)",
+    month = may # " 31--2 " # jun,
+    year = "2021",
+    address = "Reykjavik, Iceland (Online)",
+    publisher = {Link{\"o}ping University Electronic Press, Sweden},
+    url = "https://aclanthology.org/2021.nodalida-main.47",
+    pages = "422--428",
+    abstract = "We present a dataset, DanFEVER, intended for multilingual misinformation research. The dataset is in Danish and has the same format as the well-known English FEVER dataset. It can be used for testing methods in multilingual settings, as well as for creating models in production for the Danish language.",
+}
+"""
+
+_DESCRIPTION = """\
+
+"""
+
+_URL = "https://media.githubusercontent.com/media/StrombergNLP/danfever/main/tsv/da_fever.tsv"
+
+
+class DanFeverConfig(datasets.BuilderConfig):
+    """BuilderConfig for DanFever"""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig DanFever.
+
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(DanFeverConfig, self).__init__(**kwargs)
+
+
+class DanFever(datasets.GeneratorBasedBuilder):
+    """DanFever dataset."""
+
+    BUILDER_CONFIGS = [
+        DanFeverConfig(name="DanFever", version=datasets.Version("1.0.0"), description="FEVER dataset for Danish"),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "claim": datasets.Value("string"),
+                    "label": datasets.features.ClassLabel(
+                        names=[
+                            "Refuted",
+                            "Supported",
+                            "NotEnoughInfo",
+                        ]
+                    ),
+                    "evidence_extract": datasets.Value("string"),
+                    "verifiable": datasets.features.ClassLabel(
+                        names=[
+                            "NotVerifiable",
+                            "Verifiable",
+                        ]
+                    ),
+                    "evidence": datasets.Value("string"),
+                    "original_id": datasets.Value("string"),
+
+                }
+            ),
+            supervised_keys=None,
+            homepage="https://stromberg.ai/publication/danfever/",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        downloaded_file = dl_manager.download_and_extract(_URL)
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_file}),
+        ]
+
+    def _generate_examples(self, filepath):
+        logger.info("⏳ Generating examples from = %s", filepath)
+        with open(filepath, encoding="utf-8") as f:
+            data_reader = csv.DictReader(f, delimiter="\t", quotechar='"')
+            guid = 0
+            for instance in data_reader:
+                instance.pop('nr.')
+                instance["original_id"] = instance.pop('id')
+                instance["id"] = str(guid)
+                yield guid, instance
+                guid += 1

dataset_infos.json

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+{"DanFever": {"description": "\n", "citation": "@inproceedings{norregaard-derczynski-2021-danfever,\n    title = \"{D}an{FEVER}: claim verification dataset for {D}anish\",\n    author = \"N{\\o}rregaard, Jeppe  and\n      Derczynski, Leon\",\n    booktitle = \"Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa)\",\n    month = may # \" 31--2 \" # jun,\n    year = \"2021\",\n    address = \"Reykjavik, Iceland (Online)\",\n    publisher = {Link{\"o}ping University Electronic Press, Sweden},\n    url = \"https://aclanthology.org/2021.nodalida-main.47\",\n    pages = \"422--428\",\n    abstract = \"We present a dataset, DanFEVER, intended for multilingual misinformation research. The dataset is in Danish and has the same format as the well-known English FEVER dataset. It can be used for testing methods in multilingual settings, as well as for creating models in production for the Danish language.\",\n}\n", "homepage": "https://stromberg.ai/publication/danfever/", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "claim": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 3, "names": ["Refuted", "Supported", "NotEnoughInfo"], "id": null, "_type": "ClassLabel"}, "evidence_extract": {"dtype": "string", "id": null, "_type": "Value"}, "verifiable": {"num_classes": 2, "names": ["NotVerifiable", "Verifiable"], "id": null, "_type": "ClassLabel"}, "evidence": {"dtype": "string", "id": null, "_type": "Value"}, "original_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "dan_fever", "config_name": "DanFever", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2940646, "num_examples": 6407, "dataset_name": "dan_fever"}}, "download_checksums": {"https://media.githubusercontent.com/media/StrombergNLP/danfever/main/tsv/da_fever.tsv": {"num_bytes": 2952080, "checksum": "4ca3e4ee85ff8e017c49cf05235c54a00655db54c5c0a728cb4015e71b4e3efa"}}, "download_size": 2952080, "post_processing_size": null, "dataset_size": 2940646, "size_in_bytes": 5892726}}