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dataset_infos.json

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+}

headline_cause.py

@@ -0,0 +1,110 @@
+# coding=utf-8
+# Copyright 2021 The HuggingFace Datasets Authors and Ilya Gusev
+#
+# 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.
+"""HeadlineCause: A Dataset of News Headlines for Detecting Casualties"""
+
+import json
+import os
+
+import datasets
+
+
+_CITATION = """
+@misc{gusev2021headlinecause,
+    title={HeadlineCause: A Dataset of News Headlines for Detecting Casualties},
+    author={Ilya Gusev and Alexey Tikhonov},
+    year={2021},
+    eprint={2108.12626},
+    archivePrefix={arXiv},
+    primaryClass={cs.CL}
+}
+"""
+
+_DESCRIPTION = "A Dataset of News Headlines for Detecting Casualties"
+_HOMEPAGE = "https://github.com/IlyaGusev/HeadlineCause"
+_URLS = {
+    "ru_simple": {
+        "train": "ru/simple/train.jsonl",
+        "val": "ru/simple/val.jsonl",
+        "test": "ru/simple/test.jsonl"
+    },
+    "ru_full": {
+        "train": "ru/full/train.jsonl",
+        "val": "ru/full/val.jsonl",
+        "test": "ru/full/test.jsonl"
+    },
+    "en_simple": {
+        "train": "en/simple/train.jsonl",
+        "val": "en/simple/val.jsonl",
+        "test": "en/simple/test.jsonl"
+    },
+    "en_full": {
+        "train": "en/full/train.jsonl",
+        "val": "en/full/val.jsonl",
+        "test": "en/full/test.jsonl",
+    }
+}
+
+
+class HeadlineCauseDataset(datasets.GeneratorBasedBuilder):
+    """HeadlineCause Dataset"""
+
+    VERSION = datasets.Version("1.1.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="ru_simple", version=VERSION, description="Russian language, Simple task"),
+        datasets.BuilderConfig(name="en_simple", version=VERSION, description="English language, Simple task"),
+        datasets.BuilderConfig(name="ru_full", version=VERSION, description="Russian language, Full task"),
+        datasets.BuilderConfig(name="en_full", version=VERSION, description="English language, Full task"),
+    ]
+
+    DEFAULT_CONFIG_NAME = "en_simple"
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "left_url": datasets.Value("string"),
+                "right_url": datasets.Value("string"),
+                "left_title": datasets.Value("string"),
+                "right_title": datasets.Value("string"),
+                "left_timestamp": datasets.Value("timestamp[s]"),
+                "right_timestamp": datasets.Value("timestamp[s]"),
+                "id": datasets.Value("string"),
+                "has_link": datasets.Value("bool"),
+                "label": datasets.Value("int8"),
+                "result": datasets.Value("string"),
+                "agreement": datasets.Value("double")
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        downloaded_files = dl_manager.download_and_extract(_URLS[self.config.name])
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["val"]}),
+        ]
+
+    def _generate_examples(self, filepath):
+        with open(filepath, encoding="utf-8") as f:
+            for row in f:
+                data = json.loads(row)
+                yield data["id"], data