Upload atypical_animacy.py

atypical_animacy.py

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+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# 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.
+
+import csv
+import json
+import os
+import pandas as pd
+import datasets
+
+_CITATION = """@article{DBLP:journals/corr/abs-2005-11140,
+  author    = {Mariona Coll Ardanuy and
+               Federico Nanni and
+               Kaspar Beelen and
+               Kasra Hosseini and
+               Ruth Ahnert and
+               Jon Lawrence and
+               Katherine McDonough and
+               Giorgia Tolfo and
+               Daniel C. S. Wilson and
+               Barbara McGillivray},
+  title     = {Living Machines: {A} study of atypical animacy},
+  journal   = {CoRR},
+  volume    = {abs/2005.11140},
+  year      = {2020},
+  url       = {https://arxiv.org/abs/2005.11140},
+  eprinttype = {arXiv},
+  eprint    = {2005.11140},
+  timestamp = {Sat, 23 Jan 2021 01:12:25 +0100},
+  biburl    = {https://dblp.org/rec/journals/corr/abs-2005-11140.bib},
+  bibsource = {dblp computer science bibliography, https://dblp.org}
+}
+"""
+
+
+_DESCRIPTION = """\
+Atypical animacy detection dataset, based on nineteenth-century sentences in English extracted from an open dataset of nineteenth-century books digitized by the British Library (available via https://doi.org/10.21250/db14, British Library Labs, 2014). 
+This dataset contains 598 sentences containing mentions of machines. Each sentence has been annotated according to the animacy and humanness of the machine in the sentence. 
+"""
+
+_HOMEPAGE = "https://bl.iro.bl.uk/concern/datasets/323177af-6081-4e93-8aaf-7932ca4a390a?locale=en"
+
+_DATASETNAME = "atypical_animacy"
+
+_LICENSE = "CC0 1.0 Universal Public Domain"
+
+_URLS = {
+    _DATASETNAME: "https://bl.iro.bl.uk/downloads/59a8c52f-e0a5-4432-9897-0db8c067627c?locale=en",
+}
+
+
+class AtypicalAnimacy(datasets.GeneratorBasedBuilder):
+    """Living Machines: A study of atypical animacy. Each sentence has been annotated according to the animacy and humanness of the target in the sentence. Additionally, the context is also provided"""
+
+    VERSION = datasets.Version("1.1.0")
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "id": datasets.Value("string"),
+                "sentence": datasets.Value("string"),
+                "context": datasets.Value("string"),
+                "target": datasets.Value("string"),
+                "animacy": datasets.Value("float"),
+                "humanness": datasets.Value("float"),
+                "offsets": [datasets.Value("int32")],
+                "date": datasets.Value("string"),
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        urls = _URLS[_DATASETNAME]
+        data_dir = dl_manager.download_and_extract(urls)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": os.path.join(
+                        data_dir, "LwM-nlp-animacy-annotations-machines19thC.tsv"
+                    ),
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        data = pd.read_csv(filepath, sep="\t", header=0)
+        for id, row in data.iterrows():
+            date = row.Date
+            sentence = row.Sentence.replace("***", "")
+            context = row.SentenceCtxt.replace("[SEP]", "").replace("***", "")
+            target = row.TargetExpression
+            animacy = float(row.animacy)
+            humanness = float(row.humanness)
+            target_start = sentence.find(target)
+            offsets = [target_start, target_start + len(target)]
+            id = row.SentenceId
+            yield id, {
+                "id": id,
+                "sentence": sentence,
+                "context": context,
+                "target": target,
+                "animacy": animacy,
+                "humanness": humanness,
+                "date": date,
+                "offsets": offsets,
+            }