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Dataset Card for Wiki-727K Dataset

Wiki-727K is a large dataset for text segmentation, automatically extracted and labeled from Wikipedia. It is designed as a sentence-level sequence labeling task for identifying semantic or topic shift in documents.

Dataset Overview

Train: 582k
Validation: 72k
Test: 73k

Features

id (string): Document ID.
ids (sequence of string): Sentence IDs for each document.
sentences (sequence of string): Sentences in each document.
titles_mask (sequence of uint8): Mask indicating if a sentence is a title (optional).
levels (sequence of uint8): Hierarchical level of each sentence (optional).
labels (sequence of class): Binary labels: semantic-continuity or semantic-shift.

Usage

The dataset can be loaded using the HuggingFace datasets library:

from datasets import load_dataset

titled_dataset = load_dataset('saeedabc/wiki727k', num_proc=8, trust_remote_code=True)

untitled_dataset = load_dataset('saeedabc/wiki727k', drop_titles=True, num_proc=8, trust_remote_code=True)

Dataset Details

Homepage: Wiki-727K GitHub

Downloads last month: 58

Total file size:

18 kB

Models trained or fine-tuned on saeedabc/wiki727k

0xKitkat/semantic-chunker-modernbert-base

Token Classification • 0.1B • Updated 3 days ago