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Sentiment Classification Dataset (JSONL)

A labelled sentiment-classification dataset in JSON Lines — 24 short product-review-style sentences balanced across positive, negative, and neutral. Fully synthetic; a fixture for testing text-classification loaders, tokenizers, and JSONL parsers.

Preview — first 25 linesjsonl
{"text": "The battery lasts all day and the screen is gorgeous.", "label": "positive"}
{"text": "Arrived two weeks late and the box was crushed.", "label": "negative"}
{"text": "It works as described. Nothing surprising either way.", "label": "neutral"}
{"text": "Best purchase I've made this year — highly recommend.", "label": "positive"}
{"text": "Stopped charging after a month. Very disappointed.", "label": "negative"}
{"text": "Setup took a while but support was helpful.", "label": "neutral"}
{"text": "Incredibly comfortable and the build quality feels premium.", "label": "positive"}
{"text": "The app crashes every time I open the settings page.", "label": "negative"}
{"text": "Does the job. Fairly average for the price.", "label": "neutral"}
{"text": "Fast shipping and exactly what I ordered.", "label": "positive"}
{"text": "Instructions were confusing and parts were missing.", "label": "negative"}
{"text": "Fine for casual use, not for anything demanding.", "label": "neutral"}
{"text": "The sound is crisp and the bass is well balanced.", "label": "positive"}
{"text": "Overpriced for what you actually get.", "label": "negative"}
{"text": "Looks nice on the desk; performance is unremarkable.", "label": "neutral"}
{"text": "Customer service replaced it without any hassle.", "label": "positive"}
{"text": "It overheats within minutes of heavy use.", "label": "negative"}
{"text": "Standard packaging, standard product, no complaints.", "label": "neutral"}
{"text": "Lightweight, sturdy, and surprisingly affordable.", "label": "positive"}
{"text": "The colours look nothing like the photos online.", "label": "negative"}
{"text": "Reasonable quality but the manual could be clearer.", "label": "neutral"}
{"text": "Exceeded my expectations in every way.", "label": "positive"}
{"text": "Broke on the second day. Would not buy again.", "label": "negative"}
{"text": "Perfectly adequate for everyday tasks.", "label": "neutral"}

Specifications

Records
24
Labels
positive, negative, neutral
Schema
text, label
Task
text classification

What is a .jsonl file?

JSONL (JSON Lines) is a text format where each line is a complete, independent JSON value, allowing records to be streamed and appended without parsing the whole file. It is not itself a JSON array and each line must stand alone. It is common in logging, machine learning datasets, and data pipelines.

How to use this file

Use an example JSONL to test line-by-line streaming parsers, append-and-resume ingestion, and batch pipelines that process one record per line.

Code examples

import json

with open("sentiment.jsonl") as f:
    rows = [json.loads(line) for line in f]
print(len(rows), rows[0])

Generated by generation/ai_datasets.py. Free for any use, no attribution required — license.