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metadata
license: agpl-3.0
task_categories:
  - text-generation
  - text-classification
language:
  - en
tags:
  - Poem
size_categories:
  - 10K<n<100K

From: https://www.kaggle.com/datasets/tgdivy/poetry-foundation-poems

Poetry Foundation Poems Dataset

Overview

This dataset contains a collection of 13.9k poems sourced from the Poetry Foundation website. Each poem entry includes its title, author, and associated tags (if available). The dataset provides a robust resource for exploring poetry, analyzing thematic trends, or creating applications such as poem generators.

Dataset Structure

The dataset consists of the following columns:

1.	Title: The title of the poem.

2.	Author: The name of the poem’s author.

3.	Tags: The thematic tags or categories associated with the poems.

Dataset Highlights

•	Size: The dataset includes 13.9k rows, with each row representing an individual poem.

•	Diversity: Poems span a wide range of topics and authors, making it a rich resource for literary and thematic exploration.

•	Tags: The tags provide a structured way to categorize and filter poems by themes, enhancing the dataset’s usability for research and creative projects.

Use Cases

1.	Poem Generation:

Train models to generate poems based on user-inputted topics or tags.

2.	Thematic and Sentiment Analysis:

Analyze trends in poetic themes, sentiments, or styles over time.

3.	NLP Tasks:

Use the dataset for text classification, clustering, or other natural language processing tasks.

4.	Educational Resources:

Develop tools or applications for poetry analysis, learning, or teaching.

5.	Visualizations:

Create word clouds or charts using the tags to identify common themes in poetry.

Technical Details

•	File Size: Approximately 13,900 rows of data.

•	Format: Typically provided in CSV or JSON format.

•	Dependencies:

•	Pandas for data manipulation.

•	NLTK or spaCy for natural language processing.

•	Matplotlib or WordCloud for creating visualizations.

Licensing

This dataset is under GNU Affero General Public License v3.0.

Acknowledgments

The dataset was compiled to provide researchers, developers, and enthusiasts with a structured collection of poetry for creative and analytical purposes. All credits go to the original authors and the Poetry Foundation for their work in making these poems accessible.

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