Datasets:

KORMo-VL
/

ko-web-understanding

language:
  - ko
task_categories:
  - image-text-to-text
  - visual-question-answering
tags:
  - web
  - gui-agent
  - screen-understanding
pretty_name: KO-Web-Understanding
configs:
  - config_name: page_caption
    data_files: data/page_caption/*.parquet
    default: true
  - config_name: screen_qa
    data_files: data/screen_qa/*.parquet
  - config_name: ocr_read_text
    data_files: data/ocr_read_text/*.parquet
  - config_name: grounding
    data_files: data/grounding/*.parquet
  - config_name: screen_change_caption
    data_files: data/screen_change_caption/*.parquet
  - config_name: action_between_screens
    data_files: data/action_between_screens/*.parquet
  - config_name: action_between_screens_think
    data_files: data/action_between_screens_think/*.parquet
  - config_name: next_action
    data_files: data/next_action/*.parquet
  - config_name: next_screen_prediction
    data_files: data/next_screen_prediction/*.parquet
  - config_name: next_screen_prediction_detailed
    data_files: data/next_screen_prediction_detailed/*.parquet

KO-Web-Understanding

Korean web screen understanding data used to train the KORMo-Web agents. Each subset is one task; pick it by name.

Text only. Screenshots are not included; image_files gives the file name of the screen(s) each row was made from.

from datasets import load_dataset
ds = load_dataset("KORMo-VL/ko-web-understanding", "grounding", split="train")

Subset	Rows	Task
`page_caption`	1,419,854	Grounded description of the whole screen (element names with 0–1000 coordinates)
`screen_qa`	506,157	Question answering about what is on the screen
`ocr_read_text`	505,638	Read the text in a given region or the whole screen
`grounding`	1,517,176	text_to_point / point_to_text / appearance_to_point (0–1000 coordinates)
`screen_change_caption`	498,731	Describe what changed between two screens and how
`action_between_screens`	499,078	Which action (click / scroll) turns screen 1 into screen 2
`action_between_screens_think`	498,517	Same as above, with reasoning
`next_action`	505,550	Next action toward a goal (click)
`next_screen_prediction`	506,005	Predict the screen after a click
`next_screen_prediction_detailed`	505,692	Predict the screen after a click or scroll, in detail
Total	6,962,398

Fields

Field	Description
`id`	Unique row id
`lang`	`ko`
`task` / `subtask`	Task name and variant (e.g. `click`, `scroll`, `text_to_point`)
`question`	User prompt
`answer`	Target answer. For action tasks, a JSON tool call such as `{"name": "click", "arguments": {"x": 500, "y": 300}}`
`reasoning`	Reasoning text when the task has one, else null
`image_files`	Screenshot file name(s) the row refers to

Coordinates are normalized to 0–1000.

Notes

Screens come from public Korean websites. Screens captured while logged in (my page, cart, checkout, mail, social media, community sites, etc.) were removed.
Session, token and password values inside URLs were replaced with [MASKED].
page_caption keeps all mid-length captions; other subsets are random samples of about 500k rows each (grounding: about 500k per variant).