Datasets:
Sub-tasks:
semantic-similarity-classification
Languages:
English
Size:
100K<n<1M
Tags:
text segmentation
document segmentation
topic segmentation
topic shift detection
semantic chunking
chunking
License:
Dataset Viewer
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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-continuityorsemantic-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
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