---

TinyStories

A Diverse, Richly Annotated Corpus of Short-Form Stories

By Huggingface Hub [source]

---

About this dataset

> This dataset contains the text of a remarkable collection of short stories known as the TinyStories Corpus. With over 2,000 annotated stories, it is populated with an array of diverse styles and genres from multiple sources. This corpus is enriched by intricate annotations across each narrative content, making it a valuable resource for narrative text classification. The text field in each row includes the entirety of each story that can be used to identify plots, characters and other features associated with story-telling techniques. Through this collection of stories, users will gain an extensive insight into a wide range of narratives which could be used to produce powerful machine learning models for Narrative Text Classification

More Datasets

> For more datasets, click here.

Featured Notebooks

> - 🚨 Your notebook can be here! 🚨!

How to use the dataset

> > In this dataset, each row contains a short story along with its associated labels for narrative text classification tasks. The data consists of the following columns: > - text: The story text itself (string) > - validation.csv: Contains a set of short stories for validation (dataframe) > - train.csv: Contains the text of short stories used for narrative text classification (dataframe) > > The data contained in both files can be used for various types of machine learning tasks related to narrative text classification. These include but are not limited to experiments such as determining story genres, predicting user reactions, sentiment analysis etc. > > To get started with using this dataset, begin by downloading both validation and train csv files from Kaggle datasets page and saving them on your computer or local environment. Once downloaded, you may need to preprocess both datasets by cleaning up any unnecessary/wrongly formatted values or duplicate entries if any exists within it before proceeding further on to your research work or machine learning task experimentations as these have great impacts on your research results accuracy rate which you do not want compromised! > > Next step is simply loading up these two datasets into Python pandas dataframes so that they can easily be manipulated and analyzed using common tools associated with Natural Language Processing(NLP). This would require you writing few simple lines using pandas API functions like read_csv(), .append(), .concat()etc depending upon what kind of analysis/experiment you intend conducting afterwards utilizing this dataset in Python Jupyter Notebook framework as well as other machine learning frameworks popular among data scientists like scikit-learn if it will be something more complex than simple NLP task operations! > > By now if done everything mentioned correctly here then we are ready now to finally get into actually working out our desired applications from exploring potential connections between different narratives or character traits via supervised Machine Learning models such as Naive Bayes Classifier among many others that could ultimately provide us useful insights revealing patterns existing underneath all those texts! With all necessary datas loaded up in supporting python platforms correctly so feel free to make interesting discoveries/predictions from extensive analyses provided by this richly annotated TinyStories Narrative Dataset!

Research Ideas

> - Creating a text classification algorithm to automatically categorize short stories by genre. > - Developing an AI-based summarization tool to quickly summarize the main points in a story. > - Developing an AI-based story generator that can generate new stories based on existing ones in the dataset

Acknowledgements

> If you use this dataset in your research, please credit the original authors. > Data Source > >

License

> > > License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication > No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: validation.csv

Column name	Description
text	The text of the story. (String)

---

File: train.csv

Column name	Description
text	The text of the story. (String)

Acknowledgements

> If you use this dataset in your research, please credit the original authors. > If you use this dataset in your research, please credit Huggingface Hub.