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:
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) | |