Delete loading script

atypical_animacy.py

@@ -1,123 +0,0 @@
-# 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 = row.Sentence.find("***")
-            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,
-            }