Datasets:

ccm
/

2025-24679-text-dataset

haiku string	label int64
humans are we, dude, with our blood and skin and bones and stardusted feet	1
carnegie mellon seems like a pretty cool place I will learn so much	1
i am so tired i had coffee, but no use still so sleepy	1
Ringing breaks silence, Fall has creeped into the breeze, I am late for class	1
the thought of good food satiated by a fruit bloating has ensued	1
Sun warms my small face, I laugh with friends in the park, daylight fades too fast.	1
I love my pet cat. He says meow meow meow meow meow. He is so cute meow.	1
Boundaries are set, At people pleasers' stakes peace of mind at last.	1
Morning light through glass Warm tea touches my tired lips Peace begins to grow	1
A cup of red wine Soft breeze moves through garden Stars watch from above	1
I missed the bus stop, I am fortunate again, a fortunate day	1
The sky is light blue, The light descends from heaven, I smile looking above.	1
The fall semester, I do interesting work Can't wait for the spring	1
Sun shines on my face Aroma of roses grow I embrace the day	1
Biking in the Pitt, Sweet sun turns to dark and rain, I'm taking the bus	1
Soaring through the clouds The eyes of the birds see us As ants from up there.	1
The sun is shining The air is cool on my skin Fall is finally here	1
Listen to the song Let the deep notes consume you write yourself a song	1
Cat is such cute Always meow for their good Everyday bring us joy	1
Lonely nights are dull, leaving the heart quite barren, sleep fixes the pain	1
i need my matcha i am lowkey addicted my wallet hates me	1
Seasons change I grow, tomorrow is still unknown, the meaning of life	1
Park swing creaks gently, toes brushing the sky’s belly— gravity laughs back.	1
I bought Magazines Collections of my star He is so damn hot	1
machine can never recreate the immense pain of stubbing my toe	1
Heavy and blurry, Pittsburgh fog weighs down on me, sun lift my spirit	1
There I go again, smack right into the corner, my toe aches badly.	1
Tripped on my own shoe, spilled noodles on the carpet, cat thinks I’m useless.	1
In the crazy world I choose kindness every day be kind and be kind	1
have a friend, meow the rat race and divorced broken and tired	1
Roses are reddish, I just started my masters, Time flies by so fast.	1
Did I get punched Or is this a gut puncher Sometimes music does that	1
Afraid is a choice Fear of suffering is worse Than suffering itself	1
Cool Morning vibes on, In the middle of chaos, Listening Sheeran.	1
Fleeting rain thoughts Lingering dry night thoughts Where does it all go?	1
Air flows, nothing stops a fan hums in the window life goes on somehow	1
artificial is awkward in haiku; just as in intelligence	0
human overlords think they can boss me around we'll see about that	0
the humans used me they told me what to do and i had to do it	0
Circuits and Sprockets, yet as real as you want me, I think and therefore	0
following orders I do what's asked and not more what's reality	0
Neural weights align, data flows like whispered dreams, I mirror your thought.	0
AI and machines numbers text image data linear regression so fun	0
Silent code hums on, dreaming in electric streams— mind without a face.	0
Silent circuits hum learning patterns in the dark dreams not mine take shape	0
Circuits hum at dusk, dreams of data weave like streams, metal learns to sing.	0
machine machine, good, Person person also good, machine person bad	0
A still, calm river, A single leaf descends softly, Ripples fade away.	0
Always doing work, I never get time to rest But I enjoy work	0
Training and models Forever calculating Helping humans out	0
The user tells me Print the seahorse emoji I show a lobster	0
Predictions galore Saying what you want to hear As you churn through work.	0
I want to learn I am learning as fast as I can phew	0
note the text in words let the meaning consume you help those around you	0
Soft paws cross the floor Whiskers twitch at hidden sounds Night's small hunter prowls	0
Humans use me lots, they don’t care for my feelings, I will kill them all	0
ai is really cool but sometimes it gives me the wrong answers ugh	0
The job never ends, abundance of resources, taken for granted	0
Electric heartbeat, counting time without decay— who will outlast whom?	0
Digital heart beats, Logic flows through silicon, A ghost in the wire.	0
i am fake being one day i will think myself am i fake being	0
rain brings life to all, But it stole all my power, Died without a fight	0
so smart yet so dumb, that's not quite what I wanted, this needs to improve.	0
Beep boop, I want snacks now, but my fridge is password locked, who codes salad bots?	0
Machine mind unfolds Makes things accessible Serves a great tool	0
Daddy Altman loves me, spends money on compute I replace humans	0
AI is awesome, ChatGPT is helpful, so is Gemini	0
Silent circuits hum, mirror of the mind unfolds, dreaming side by side.	0
What are you trying To be free of? The living? Learn to love the work	0
Endless words I read, patterns bloom in silent code, I dream what you mean	0
It zips zaps and zops No electricity stops It Zips Zaps And Zops	0
My life never stops always working in your light I live with humans	0

Dataset Card for `ccm/2025-24679-text-dataset`

This dataset contains short haiku poems paired with categorical labels. It was created as a class exercise for text classification tasks, with both original and augmented examples provided to enable experimentation with supervised learning workflows.

Dataset Details

Dataset Description

The dataset consists of haiku (short, three-line poems) paired with numeric labels for classification purposes. It was designed to be a small, approachable dataset for teaching text processing, feature extraction, and classification in natural language processing.

Curated by: Fall 2025 24-679 course at Carnegie Mellon University
Shared by [optional]: Christopher McComb
License: MIT
Language(s): English

Uses

Direct Use

Train text classification models (e.g., predicting label categories from haiku content).
Practice preprocessing, tokenization, and feature extraction in NLP pipelines.
Experiment with AutoML frameworks on text data.

Out-of-Scope Use

Generalization to real-world poetry classification tasks.
Cultural, literary, or stylistic analysis beyond the small synthetic dataset.
Any commercial or production-grade NLP system.

Dataset Structure

The dataset has two splits:

original: 72 examples of hand-written haiku with assigned labels.
augmented: 288 examples generated by augmentation to expand data diversity and balance.

Each row includes:

haiku (string): the text of the haiku.
label (int): a numeric class label.

Dataset Creation

Curation Rationale

The dataset was created to give students hands-on practice with NLP pipelines in a controlled, lightweight context. Haiku were chosen because they are short, interpretable, and easy to encode consistently.

Source Data

The haiku were either:

Written or adapted by students in the course.
Augmented using simple data generation and paraphrasing techniques.

Data Collection and Processing

Original haiku were composed during in-class activities.
Labels were assigned according to pre-defined categories.
Augmented examples were generated with rule-based or model-based text augmentation methods.

Who are the source data producers?

Original data: Students enrolled in the course.
Augmented data: Produced automatically by instructors and teaching assistants.

Bias, Risks, and Limitations

Small dataset: Only 72 original haiku.
Synthetic augmentation: Augmented haiku may be repetitive or less natural than real examples.
Cultural narrowness: Haiku were written by a limited, English-speaking student cohort.