---
language:
- en
license: mit
size_categories:
- n<1K
task_categories:
- text-generation
tags:
- geo
- seo
- search-engine-optimization
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
dataset_info:
  features:
  - name: doc_id
    dtype: string
  - name: url
    dtype: string
  - name: html_source
    dtype: string
  - name: cleaned_text
    dtype: string
  - name: cleaned_text_length
    dtype: int64
  - name: topic_tags
    sequence: string
  - name: primary_topic
    dtype: string
  - name: difficulty_tags
    sequence: string
  - name: intent_tags
    sequence: string
  - name: data_source
    dtype: string
  - name: is_html_parse_failed
    dtype: bool
  - name: needs_refetch
    dtype: bool
  - name: refetch_success
    dtype: bool
  - name: html_issues
    sequence: string
  - name: issue_score
    dtype: float64
  - name: query
    dtype: string
  - name: title
    dtype: string
  splits:
  - name: train
    num_bytes: 1792776
    num_examples: 200
  download_size: 988916
  dataset_size: 1792776
---

# GEO HTML 200 Dataset

A curated dataset of 200 web documents for Generative Engine Optimization (GEO) research.

## Features

| Column | Description |
|--------|-------------|
| doc_id | Unique document identifier |
| url | Source URL |
| cleaned_text | Parsed plain text content |
| cleaned_text_length | Character count |
| query | Associated search query |
| title | Document title |
| topic_tags | Topic classification |

## Usage

```python
from datasets import load_dataset
ds = load_dataset("erv1n/geo_html_200")
```