README.md

metadata

license: mit
task_categories:
  - other

PageGuide Dataset

This repository contains the dataset for PageGuide, a browser extension that assists users in navigating webpages and locating information by grounding LLM answers directly in the HTML DOM.

• Project Page: pageguide.github.io
• Paper: PageGuide: Browser extension to assist users in navigating a webpage and locating information
• Code: github.com/tin-xai/pageguide

Dataset Description

The PageGuide evaluation utilizes several distinct datasets representing different tasks:

1. pageguide_userstudy: Raw interaction logs from the user study — completion times, chat transcripts, correctness labels, paired statistical results, and post-study survey responses.
2. pageguide_find_data: 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.
3. pageguide_guide_data: 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.
4. pageguide_hide_data: 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

You can load these datasets using the Hugging Face datasets library:

User Study Data

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()

Find Task Data

from datasets import load_dataset
find_tasks = load_dataset("ttn0011/pageguide_find_data", split="train").to_pandas()

Guide Task Data

from datasets import load_dataset
guide_tasks = load_dataset("ttn0011/pageguide_guide_data", split="train").to_pandas()

Hide Task Data

from datasets import load_dataset
hide_tasks = load_dataset("ttn0011/pageguide_hide_data", split="train").to_pandas()