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---
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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