README.md

---
task_categories:
- other
license: mit
---

# PageGuide Dataset

This repository contains dataset artifacts from the paper [PageGuide: Browser extension to assist users in navigating a webpage and locating information](https://huggingface.co/papers/2604.23772).

* **Project Page:** https://pageguide.github.io/
* **Repository:** https://github.com/tin-xai/pageguide
* **Paper:** [Hugging Face Paper Page](https://huggingface.co/papers/2604.23772)

---

## Dataset Description

PageGuide was evaluated in a controlled within-subjects user study. The evaluation data is structured into four datasets:

### 1. `pageguide_userstudy`
* **Purpose:** Raw interaction logs from the user study — completion times, chat transcripts, correctness labels, paired statistical results, and post-study survey responses.
* **Sample Usage:**
```python
from datasets import load_dataset
tasks  = load_dataset("ttn0011/pageguide_userstudy", data_files="tasks.csv", split="train").to_pandas()
paired = load_dataset("ttn0011/pageguide_userstudy", data_files="paired_times.csv", split="train").to_pandas()
```

### 2. `pageguide_find_data`
* **Purpose:** Task stimuli for the **Find** condition — 10 real webpages (NASA, Wikipedia, Cleveland Clinic, WWF, Britannica, JMLR) each annotated with up to 2 factual questions, ground-truth answers, and supporting evidence spans.
* **Sample Usage:**
```python
from datasets import load_dataset
find_tasks = load_dataset("ttn0011/pageguide_find_data", split="train").to_pandas()
```

### 3. `pageguide_guide_data`
* **Purpose:** Task stimuli for the **Guide** condition — 7 procedural tasks across 6 platforms (Google Sheets, Google Docs, Google Slides, Coda, TradingView, Scratch), labelled Easy or Medium difficulty.
* **Sample Usage:**
```python
from datasets import load_dataset
guide_tasks = load_dataset("ttn0011/pageguide_guide_data", split="train").to_pandas()
```

### 4. `pageguide_hide_data`
* **Purpose:** Task stimuli for the **Hide** condition — 37 annotated webpage snapshots (Amazon, Netflix, TechCrunch, Allrecipes, Spotify, Yelp, and more) with `(user_goal, hide_query, difficulty, hidden_elements)` annotations and ground-truth CSS selectors.
* **Sample Usage:**
```python
from datasets import load_dataset
hide_tasks = load_dataset("ttn0011/pageguide_hide_data", split="train").to_pandas()
```