Datasets:
Commit
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Convert dataset to Parquet (#1)
Browse files- Delete loading script (cbc4306f74669628b14c84ca9f3d86d3b8c5dc95)
- Convert dataset to Parquet (ee85adcee627c5ced51735a34d1977a09d5f49b0)
- Delete legacy dataset_infos.json (18c6c57257e5c2990a7d9fa223b6cfc993e56862)
- README.md +32 -4
- atypical_animacy.py +0 -123
- data/train-00000-of-00001.parquet +3 -0
- dataset_infos.json +0 -1
README.md
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---
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annotations_creators:
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- expert-generated
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-
language:
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- en
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language_creators:
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- machine-generated
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license:
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- cc0-1.0
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multilinguality:
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- monolingual
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paperswithcode_id: null
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pretty_name: Atypical Animacy
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size_categories:
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- n<1K
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source_datasets:
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task_ids:
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- sentiment-classification
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- intent-classification
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---
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# Dataset Card for atypical_animacy
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---
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annotations_creators:
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- expert-generated
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language_creators:
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- machine-generated
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language:
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- en
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license:
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- cc0-1.0
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multilinguality:
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- monolingual
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size_categories:
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- n<1K
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source_datasets:
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task_ids:
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- sentiment-classification
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- intent-classification
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pretty_name: Atypical Animacy
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dataset_info:
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features:
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- name: id
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dtype: string
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- name: sentence
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dtype: string
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- name: context
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dtype: string
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- name: target
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dtype: string
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- name: animacy
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dtype: float32
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- name: humanness
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dtype: float32
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- name: offsets
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list: int32
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- name: date
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dtype: string
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splits:
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- name: train
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num_bytes: 442217
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num_examples: 594
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download_size: 299650
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dataset_size: 442217
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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---
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# Dataset Card for atypical_animacy
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atypical_animacy.py
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# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import csv
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import json
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import os
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import pandas as pd
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import datasets
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_CITATION = """@article{DBLP:journals/corr/abs-2005-11140,
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author = {Mariona Coll Ardanuy and
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Federico Nanni and
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Kaspar Beelen and
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Kasra Hosseini and
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Ruth Ahnert and
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Jon Lawrence and
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Katherine McDonough and
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Giorgia Tolfo and
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Daniel C. S. Wilson and
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Barbara McGillivray},
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title = {Living Machines: {A} study of atypical animacy},
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journal = {CoRR},
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volume = {abs/2005.11140},
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year = {2020},
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url = {https://arxiv.org/abs/2005.11140},
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eprinttype = {arXiv},
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eprint = {2005.11140},
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timestamp = {Sat, 23 Jan 2021 01:12:25 +0100},
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biburl = {https://dblp.org/rec/journals/corr/abs-2005-11140.bib},
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bibsource = {dblp computer science bibliography, https://dblp.org}
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}
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"""
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_DESCRIPTION = """\
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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).
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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.
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"""
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_HOMEPAGE = "https://bl.iro.bl.uk/concern/datasets/323177af-6081-4e93-8aaf-7932ca4a390a?locale=en"
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_DATASETNAME = "atypical_animacy"
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_LICENSE = "CC0 1.0 Universal Public Domain"
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_URLS = {
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_DATASETNAME: "https://bl.iro.bl.uk/downloads/59a8c52f-e0a5-4432-9897-0db8c067627c?locale=en",
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}
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class AtypicalAnimacy(datasets.GeneratorBasedBuilder):
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"""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"""
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VERSION = datasets.Version("1.1.0")
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def _info(self):
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features = datasets.Features(
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{
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"id": datasets.Value("string"),
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"sentence": datasets.Value("string"),
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"context": datasets.Value("string"),
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"target": datasets.Value("string"),
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"animacy": datasets.Value("float"),
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"humanness": datasets.Value("float"),
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"offsets": [datasets.Value("int32")],
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"date": datasets.Value("string"),
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}
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)
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=features,
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homepage=_HOMEPAGE,
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license=_LICENSE,
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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urls = _URLS[_DATASETNAME]
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data_dir = dl_manager.download_and_extract(urls)
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={
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"filepath": os.path.join(
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data_dir, "LwM-nlp-animacy-annotations-machines19thC.tsv"
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),
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},
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),
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]
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def _generate_examples(self, filepath):
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data = pd.read_csv(filepath, sep="\t", header=0)
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for id, row in data.iterrows():
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date = row.Date
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sentence = row.Sentence.replace("***", "")
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context = row.SentenceCtxt.replace("[SEP]", "").replace("***", "")
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target = row.TargetExpression
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animacy = float(row.animacy)
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humanness = float(row.humanness)
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target_start = row.Sentence.find("***")
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offsets = [target_start, target_start + len(target)]
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id = row.SentenceId
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yield id, {
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"id": id,
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"sentence": sentence,
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"context": context,
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"target": target,
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"animacy": animacy,
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"humanness": humanness,
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"date": date,
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"offsets": offsets,
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}
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data/train-00000-of-00001.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:ccb854633b8a4701169b9e521d22d308272349a2220dad87982bdf5ed2f58010
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size 299650
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dataset_infos.json
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{"default": {"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). \nThis 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. \n", "citation": "@article{DBLP:journals/corr/abs-2005-11140,\n author = {Mariona Coll Ardanuy and\n Federico Nanni and\n Kaspar Beelen and\n Kasra Hosseini and\n Ruth Ahnert and\n Jon Lawrence and\n Katherine McDonough and\n Giorgia Tolfo and\n Daniel C. S. Wilson and\n Barbara McGillivray},\n title = {Living Machines: {A} study of atypical animacy},\n journal = {CoRR},\n volume = {abs/2005.11140},\n year = {2020},\n url = {https://arxiv.org/abs/2005.11140},\n eprinttype = {arXiv},\n eprint = {2005.11140},\n timestamp = {Sat, 23 Jan 2021 01:12:25 +0100},\n biburl = {https://dblp.org/rec/journals/corr/abs-2005-11140.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n", "homepage": "https://bl.iro.bl.uk/concern/datasets/323177af-6081-4e93-8aaf-7932ca4a390a?locale=en", "license": "CC0 1.0 Universal Public Domain", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "sentence": {"dtype": "string", "id": null, "_type": "Value"}, "context": {"dtype": "string", "id": null, "_type": "Value"}, "target": {"dtype": "string", "id": null, "_type": "Value"}, "animacy": {"dtype": "float32", "id": null, "_type": "Value"}, "humanness": {"dtype": "float32", "id": null, "_type": "Value"}, "offsets": [{"dtype": "int32", "id": null, "_type": "Value"}], "date": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "atypical_animacy", "config_name": "default", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 442217, "num_examples": 594, "dataset_name": "atypical_animacy"}}, "download_checksums": {"https://bl.iro.bl.uk/downloads/59a8c52f-e0a5-4432-9897-0db8c067627c?locale=en": {"num_bytes": 144694, "checksum": "2b5a84370e298214a864683a172f854cb7a21f55684655cb4eef976b36a439f6"}}, "download_size": 144694, "post_processing_size": null, "dataset_size": 442217, "size_in_bytes": 586911}}
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