README.md

metadata

annotations_creators:
  - expert-generated
language_creators:
  - found
languages:
  - en
licenses:
  - cc-by-4.0
multilinguality:
  - monolingual
size_categories:
  - 1K<n<10K
source_datasets:
  - original
task_categories:
  - text-classification
task_ids:
  - sentiment-classification
paperswithcode_id: gutenberg-poem-dataset
pretty_name: Gutenberg Poem Dataset
train-eval-index:
  - config: default
    task: text-classification
    task_id: multi_class_classification
    splits:
      train_split: train
      eval_split: test
    col_mapping:
      verse_text: text
      label: target
    metrics:
      - type: accuracy
        name: Accuracy
      - type: f1
        name: F1 macro
        args:
          average: macro
      - type: f1
        name: F1 micro
        args:
          average: micro
      - type: f1
        name: F1 weighted
        args:
          average: weighted
      - type: precision
        name: Precision macro
        args:
          average: macro
      - type: precision
        name: Precision micro
        args:
          average: micro
      - type: precision
        name: Precision weighted
        args:
          average: weighted
      - type: recall
        name: Recall macro
        args:
          average: macro
      - type: recall
        name: Recall micro
        args:
          average: micro
      - type: recall
        name: Recall weighted
        args:
          average: weighted

Dataset Card for Gutenberg Poem Dataset

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • Contributions

Dataset Description

• Homepage: N/A
• Repository: GitHub
• Paper: Investigating Societal Biases in a Poetry Composition System
• Leaderboard: N/A
• Point of Contact: -

Dataset Summary

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.

Supported Tasks and Leaderboards

[More Information Needed]

Languages

The text in the dataset is in English (en).

Dataset Structure

Data Instances

Example of one instance in the dataset.

{'id': 0, 'label': 2, 'verse_text': 'with pale blue berries. in these peaceful shades--'}

Data Fields

• id: index of the example
• verse_text: The text of the poem verse
• label: The sentiment label. Here
  • 0 = negative
  • 1 = positive
  • 2 = no impact
  • 3 = mixed (both negative and positive)

    Note: The original dataset uses different label indices (negative = -1, no impact = 0, positive = 1)

Data Splits

The dataset is split into a train, validation, and test split with the following sizes:

	train	validation	test
Number of examples	892	105	104

[More Information Needed]

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

[More Information Needed]

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

[More Information Needed]

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

This work is licensed under a Creative Commons Attribution 4.0 International License

Citation Information

@misc{sheng2020investigating,
      title={Investigating Societal Biases in a Poetry Composition System},
      author={Emily Sheng and David Uthus},
      year={2020},
      eprint={2011.02686},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

Contributions

Thanks to @patil-suraj for adding this dataset.