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:
File size: 2,374 Bytes
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---
annotations_creators:
- machine-generated
language_creators:
- found
language:
- en
license:
- mit
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- text-classification
- sentence-similarity
task_ids:
- semantic-similarity-classification
pretty_name: Wiki-727K
tags:
- text segmentation
- document segmentation
- topic segmentation
- topic shift detection
- semantic chunking
- chunking
- nlp
- wikipedia
dataset_info:
features:
- name: id
dtype: string
- name: ids
sequence: string
- name: sentences
sequence: string
- name: titles_mask
sequence: uint8
- name: levels
sequence: uint8
- name: labels
sequence:
class_label:
names:
'0': semantic-continuity
'1': semantic-shift
splits:
- name: train
num_bytes: 4754764877
num_examples: 582160
- name: validation
num_bytes: 595209014
num_examples: 72354
- name: test
num_bytes: 608033007
num_examples: 73232
download_size: 1569504207
dataset_size: 5958006898
---
# 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:
```python
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](https://github.com/koomri/text-segmentation)
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