Create sv-ident.py

sv-ident.py

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+# coding=utf-8
+# Copyright 2020 The TensorFlow Datasets Authors and the 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
+"""Survey Variable Identification (SV-Ident) Corpus."""
+
+import csv
+import random
+
+import datasets
+
+
+# TODO: Add BibTeX citation
+_CITATION = """\
+@misc{sv-ident,
+    author={vadis-project},
+    title={SV-Ident},
+    year={2022},
+    url={https://github.com/vadis-project/sv-ident},
+    }
+"""
+
+_DESCRIPTION = """\
+The SV-Ident corpus (version 0.3) is a collection of 4,248 expert-annotated English
+and German sentences from social science publications, supporting the task of
+multi-label text classification.
+"""
+
+_HOMEPAGE = "https://github.com/vadis-project/sv-ident"
+
+# TODO: Add the licence
+# _LICENSE = ""
+
+_URLS = {
+    "train": "https://raw.githubusercontent.com/vadis-project/sv-ident/9962c3274444ce84c59d42e2a6f8c0958ed15a26/data/train/data.tsv",
+    "trial": "https://github.com/vadis-project/sv-ident/tree/9962c3274444ce84c59d42e2a6f8c0958ed15a26/data/trial",
+}
+
+
+class SVIdent(datasets.GeneratorBasedBuilder):
+    """Survey Variable Identification (SV-Ident) Corpus."""
+
+    VERSION = datasets.Version("0.3.0")
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "sentence": datasets.Value("string"),
+                "is_variable": datasets.ClassLabel(names=["0", "1"]),
+                "variable": datasets.Sequence(datasets.Value(dtype="string")),
+                "research_data": datasets.Sequence(datasets.Value(dtype="string")),
+                "doc_id": datasets.Value("string"),
+                "uuid": datasets.Value("string"),
+                "lang": datasets.Value("string"),
+            }
+        )
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            supervised_keys=("sentence", "is_variable"),
+            homepage=_HOMEPAGE,
+            # license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        filepath = dl_manager.download(_URLS["train"])
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": filepath,
+                },
+            )
+        ]
+
+    def _generate_examples(self, filepath):
+        """Yields examples."""
+        data = []
+        with open(filepath, newline="", encoding="utf-8") as csvfile:
+            reader = csv.reader(csvfile, delimiter="\t")
+            next(reader, None)  # skip the headers
+            for row in reader:
+                data.append(row)
+
+        seed = 42
+        random.seed(seed)
+        random.shuffle(data)
+
+        for id_, example in enumerate(data):
+            sentence = example[0]
+            is_variable = example[1]
+            variable = example[2] if example[2] != "" else []
+            if variable:
+                variable = variable.split(";") if ";" in variable else [variable]
+            research_data = example[3] if example[3] != "" else []
+            if research_data:
+                research_data = research_data.split(";") if ";" in research_data else [research_data]
+            doc_id = example[4]
+            uuid = example[5]
+            lang = example[6]
+
+            yield id_, {
+                "sentence": sentence,
+                "is_variable": is_variable,
+                "variable": variable,
+                "research_data": research_data,
+                "doc_id": doc_id,
+                "uuid": uuid,
+                "lang": lang,
+            }