Datasets:
Sub-tasks:
semantic-similarity-classification
Languages:
English
Size:
10K<n<100K
Tags:
text segmentation
document segmentation
topic segmentation
topic shift detection
semantic chunking
chunking
License:
File size: 3,684 Bytes
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---
annotations_creators:
- machine-generated
language_creators:
- found
language:
- en
license:
- mit
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
- sentence-similarity
task_ids:
- semantic-similarity-classification
pretty_name: WikiSection (en_city, en_disease)
tags:
- text segmentation
- document segmentation
- topic segmentation
- topic shift detection
- semantic chunking
- chunking
- nlp
- wikipedia
dataset_info:
- config_name: en_city
features:
- name: id
dtype: string
- name: title
dtype: string
- name: ids
sequence: string
- name: sentences
sequence: string
- name: titles_mask
sequence: uint8
- name: labels
sequence:
class_label:
names:
'0': semantic-continuity
'1': semantic-shift
splits:
- name: train
num_bytes: 105236889
num_examples: 13679
- name: validation
num_bytes: 15693016
num_examples: 1953
- name: test
num_bytes: 31140798
num_examples: 3907
download_size: 94042594
dataset_size: 152070703
- config_name: en_disease
features:
- name: id
dtype: string
- name: title
dtype: string
- name: ids
sequence: string
- name: sentences
sequence: string
- name: titles_mask
sequence: uint8
- name: labels
sequence:
class_label:
names:
'0': semantic-continuity
'1': semantic-shift
splits:
- name: train
num_bytes: 22409988
num_examples: 2513
- name: validation
num_bytes: 3190201
num_examples: 359
- name: test
num_bytes: 6088470
num_examples: 718
download_size: 94042594
dataset_size: 31688659
---
# Dataset Card for WikiSection (en_city, en_disease) Dataset
The WikiSection dataset is a collection of segmented Wikipedia articles related to cities and diseases, structured in this repository for a sentence-level document segmentation task.
## Dataset Overview
WikiSection contains two English subsets:
- **en_city**: 19.5k Wikipedia articles about cities and city-related topics.
- **en_disease**: 3.6k articles on diseases and health-related scientific information.
Each subset provides segmented articles, where the task is to classify sentence boundaries as either "semantic-continuity" or "semantic-shift."
## Features
The dataset provides the following features:
- **id**: `string` - A unique identifier for each document.
- **title**: `string` - The title of the document.
- **ids**: `list[string]` - The sentence ids within the document
- **sentences**: `list[string]` - The sentences within the document.
- **titles_mask**: `list[uint8]` - A binary mask to indicate which sentences are titles.
- **labels**: `list[int]` - Binary labels for each sentence, where `0` represents "semantic-continuity" and `1` represents "semantic-shift."
## Usage
The dataset can be easily loaded using the HuggingFace `datasets` library:
```python
from datasets import load_dataset
# en_city
titled_en_city = load_dataset('saeedabc/wikisection', 'en_city', trust_remote_code=True)
untitled_en_city = load_dataset('saeedabc/wikisection', 'en_city', drop_titles=True, trust_remote_code=True)
# en_disease
titled_en_disease = load_dataset('saeedabc/wikisection', 'en_disease', trust_remote_code=True)
untitled_en_disease = load_dataset('saeedabc/wikisection', 'en_disease', drop_titles=True, trust_remote_code=True)
```
## Dataset Details
- **Homepage**: [WikiSection on GitHub](https://github.com/sebastianarnold/WikiSection)
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