Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
sentiment-classification
Languages:
English
Size:
1K - 10K
ArXiv:
License:
Commit
•
ca8fca8
0
Parent(s):
Update files from the datasets library (from 1.2.0)
Browse filesRelease notes: https://github.com/huggingface/datasets/releases/tag/1.2.0
- .gitattributes +27 -0
- README.md +166 -0
- dataset_infos.json +1 -0
- dummy/1.0.0/dummy_data.zip +3 -0
- poem_sentiment.py +85 -0
.gitattributes
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README.md
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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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- found
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languages:
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- en
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licenses:
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- cc-by-4-0
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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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- original
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task_categories:
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- text-classification
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task_ids:
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- sentiment-classification
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---
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# Dataset Card Creation Guide
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## Table of Contents
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- [Dataset Description](#dataset-description)
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- [Dataset Summary](#dataset-summary)
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- [Supported Tasks](#supported-tasks-and-leaderboards)
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- [Languages](#languages)
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- [Dataset Structure](#dataset-structure)
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- [Data Instances](#data-instances)
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- [Data Fields](#data-instances)
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- [Data Splits](#data-instances)
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- [Dataset Creation](#dataset-creation)
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- [Curation Rationale](#curation-rationale)
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- [Source Data](#source-data)
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- [Annotations](#annotations)
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- [Personal and Sensitive Information](#personal-and-sensitive-information)
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- [Considerations for Using the Data](#considerations-for-using-the-data)
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- [Social Impact of Dataset](#social-impact-of-dataset)
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- [Discussion of Biases](#discussion-of-biases)
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- [Other Known Limitations](#other-known-limitations)
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- [Additional Information](#additional-information)
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- [Dataset Curators](#dataset-curators)
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- [Licensing Information](#licensing-information)
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- [Citation Information](#citation-information)
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## Dataset Description
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- **Homepage:** N/A
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- **Repository:** [GitHub](https://github.com/google-research-datasets/poem-sentiment)
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- **Paper:** [Investigating Societal Biases in a Poetry Composition System](https://arxiv.org/abs/2011.02686)
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- **Leaderboard:** N/A
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- **Point of Contact:** -
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### Dataset Summary
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Poem Sentiment is a sentiment dataset of poem verses from Project Gutenberg.
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This dataset can be used for tasks such as sentiment classification or style transfer for poems.
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### Supported Tasks and Leaderboards
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[More Information Needed]
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### Languages
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The text in the dataset is in English (`en`).
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## Dataset Structure
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### Data Instances
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Example of one instance in the dataset.
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```{'id': 0, 'label': 2, 'verse_text': 'with pale blue berries. in these peaceful shades--'}```
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### Data Fields
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- `id`: index of the example
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- `verse_text`: The text of the poem verse
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- `label`: The sentiment label. Here
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- 0 = negative
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- 1 = positive
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- 2 = no impact
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- 3 = mixed (both negative and positive)
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> Note: The original dataset uses different label indices (negative = -1, no impact = 0, positive = 1)
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### Data Splits
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The dataset is split into a `train`, `validation`, and `test` split with the following sizes:
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| | Tain | Valid | Test |
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| ----- | ------ | ----- | ----- |
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| Number of examples | 892 | 105 | 104 |
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[More Information Needed]
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## Dataset Creation
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### Curation Rationale
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[More Information Needed]
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### Source Data
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[More Information Needed]
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#### Initial Data Collection and Normalization
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[More Information Needed]
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#### Who are the source language producers?
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[More Information Needed]
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### Annotations
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[More Information Needed]
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#### Annotation process
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[More Information Needed]
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#### Who are the annotators?
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[More Information Needed]
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### Personal and Sensitive Information
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[More Information Needed]
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## Considerations for Using the Data
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### Social Impact of Dataset
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[More Information Needed]
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136 |
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### Discussion of Biases
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[More Information Needed]
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### Other Known Limitations
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[More Information Needed]
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## Additional Information
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### Dataset Curators
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[More Information Needed]
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### Licensing Information
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This work is licensed under a Creative Commons Attribution 4.0 International License
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### Citation Information
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```
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@misc{sheng2020investigating,
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title={Investigating Societal Biases in a Poetry Composition System},
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author={Emily Sheng and David Uthus},
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year={2020},
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eprint={2011.02686},
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archivePrefix={arXiv},
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primaryClass={cs.CL}
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}
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```
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dataset_infos.json
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{"default": {"description": "Poem Sentiment is a sentiment dataset of poem verses from Project Gutenberg. This dataset can be used for tasks such as sentiment classification or style transfer for poems.\n", "citation": "@misc{sheng2020investigating,\n title={Investigating Societal Biases in a Poetry Composition System},\n author={Emily Sheng and David Uthus},\n year={2020},\n eprint={2011.02686},\n archivePrefix={arXiv},\n primaryClass={cs.CL}\n}\n", "homepage": "https://github.com/google-research-datasets/poem-sentiment", "license": "", "features": {"id": {"dtype": "int32", "id": null, "_type": "Value"}, "verse_text": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 3, "names": ["negative", "positive", "no_impact"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "builder_name": "poem_sentiment", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 48555, "num_examples": 892, "dataset_name": "poem_sentiment"}, "validation": {"name": "validation", "num_bytes": 5788, "num_examples": 105, "dataset_name": "poem_sentiment"}, "test": {"name": "test", "num_bytes": 5588, "num_examples": 104, "dataset_name": "poem_sentiment"}}, "download_checksums": {"https://raw.githubusercontent.com/google-research-datasets/poem-sentiment/master/data//train.tsv": {"num_bytes": 40567, "checksum": "09503a850796736a8e63504ae2c8de983f57dceebc2342ea93a7f7ad06af56d0"}, "https://raw.githubusercontent.com/google-research-datasets/poem-sentiment/master/data//dev.tsv": {"num_bytes": 4747, "checksum": "0770bd7b80e04c92da82e78f9f93ce35d38b334b4830fca2b9b4d7e174f152e5"}, "https://raw.githubusercontent.com/google-research-datasets/poem-sentiment/master/data//test.tsv": {"num_bytes": 4556, "checksum": "a406d87b62a6b7c9615468a8b66e69c027fa8f2f03a4f8f6c79df26c260de620"}}, "download_size": 49870, "post_processing_size": null, "dataset_size": 59931, "size_in_bytes": 109801}}
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dummy/1.0.0/dummy_data.zip
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version https://git-lfs.github.com/spec/v1
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oid sha256:eca1c5d23c979bee4a312690c71cd2653e0da100f08d61d392766cf075181a11
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size 964
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poem_sentiment.py
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# coding=utf-8
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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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"""Poem Sentiment: A sentiment dataset of poem verses"""
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from __future__ import absolute_import, division, print_function
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import datasets
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_CITATION = """\
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@misc{sheng2020investigating,
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title={Investigating Societal Biases in a Poetry Composition System},
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author={Emily Sheng and David Uthus},
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year={2020},
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eprint={2011.02686},
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archivePrefix={arXiv},
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primaryClass={cs.CL}
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}
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"""
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_DESCRIPTION = """\
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Poem Sentiment is a sentiment dataset of poem verses from Project Gutenberg. \
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This dataset can be used for tasks such as sentiment classification or style transfer for poems.
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"""
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_HOMEPAGE = "https://github.com/google-research-datasets/poem-sentiment"
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_BASE_URL = "https://raw.githubusercontent.com/google-research-datasets/poem-sentiment/master/data/"
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_URLS = {
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"train": f"{_BASE_URL}/train.tsv",
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"dev": f"{_BASE_URL}/dev.tsv",
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"test": f"{_BASE_URL}/test.tsv",
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}
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_LABEL_MAPPING = {-1: 0, 0: 2, 1: 1, 2: 3}
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class PoemSentiment(datasets.GeneratorBasedBuilder):
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"""Poem Sentiment: A sentiment dataset of poem verses"""
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VERSION = datasets.Version("1.0.0")
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def _info(self):
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=datasets.Features(
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{
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"id": datasets.Value("int32"),
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"verse_text": datasets.Value("string"),
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"label": datasets.ClassLabel(names=["negative", "positive", "no_impact", "mixed"]),
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}
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),
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supervised_keys=None,
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homepage=_HOMEPAGE,
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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downloaded_files = dl_manager.download(_URLS)
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return [
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
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datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
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datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
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]
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def _generate_examples(self, filepath):
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with open(filepath, encoding="utf-8") as f:
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lines = f.readlines()
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for line in lines:
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fields = line.strip().split("\t")
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idx, verse_text, label = fields
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84 |
+
label = _LABEL_MAPPING[int(label)]
|
85 |
+
yield int(idx), {"id": int(idx), "verse_text": verse_text, "label": label}
|