Datasets:
File size: 4,681 Bytes
d8fbf3d |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 |
# 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,
}
|