---
license: cc-by-4.0
language:
- en
task_categories:
- image-to-text
size_categories:
- n<1K
pretty_name: Resume Parsing (Vision, Synthetic)
tags:
- synthetic
- resume
- document-ai
- vision
- information-extraction
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train.parquet
  - split: validation
    path: data/validation.parquet
  - split: test
    path: data/test.parquet
---

# Resume Parsing (Vision, Synthetic)

A **fully synthetic** vision dataset for resume parsing: rendered resume page images paired
with the ground-truth structured JSON they encode. Companion to the
[`sukhrobnurali/qwen3vl-resume-parser`](https://huggingface.co/sukhrobnurali/qwen3vl-resume-parser) model.

> **Release v1.0: the complete 1000-sample dataset.** Splits are frozen (see below), so any future additions never move an existing sample between splits.

## What each sample contains

| Field | Description |
| --- | --- |
| `images` | The 1-3 rendered resume page PNGs (the model input). |
| `ground_truth` | The 23-field canonical resume record as a JSON string (the parse target). |
| `resume_text` | The rendered resume as plain text (for text-only baselines). |
| `sample_id`, `desired_position`, `years_experience`, `num_pages`, `template_id`, `theme_id`, `languages`, `split` | Flat metadata for browsing and filtering. |

The 23 ground-truth fields: `first_name`, `last_name`, `date_of_birth`, `email`, `phone`,
`desired_position`, `about`, `job_experience`, `job_expectations`, `min_salary`, `max_salary`,
`ready_to_relocation`, `work_modes`, `employment_types`, `employment_durations`, `hobbies`,
`address`, `skills`, `experiences`, `educations`, `languages`, `certificates`, `projects`.

## How it was generated

Each resume is built **structured-first**: code authors every classified/canonical value (role,
dates, countries, salaries, skills, languages, contact details) and its surface form. A language
model writes **only** free-text prose and fictional identity strings (names, company and
institution names, summaries, descriptions) — it never invents the classified fields. The record
is rendered to HTML, then to page PNGs across 3 layouts x 4 themes, and passed through automated
QC gates (JSON-schema, enum, text-fidelity, persona de-duplication, and rendered-page-count). Only
samples that pass every gate are kept. The canonical JSON is therefore authored, never parsed back
from a document, so labels are exact by construction.

## Splits

Frozen, employer-overlap-free splits at the final 85%/8%/8% proportions:

| Split | Samples |
| --- | --- |
| train | 850 |
| validation | 75 |
| test | 75 |

Samples linked by a shared (fictional) employer are kept together in one split, so no employer
spans two splits. Each sample's split is fixed in the generation ledger; future releases only
assign newly added samples, so a sample published here keeps its split forever.

## Privacy: no real personal data

This dataset contains **no real personal data**. Every name, company, and institution is
fictional; e-mail addresses use the RFC 2606 reserved domain `example.com`; phone numbers use the
reserved `555-01xx` fictional block. It is **not** derived from any real candidate corpus. It is
intended as a privacy-safe, redistributable substitute for resume-parsing work.

## Composition (this release)

- **1000** resumes spanning **32** software-industry roles.
- Experience: 0-25 years (mean 7.9).
- Pages per resume: 1pg x207, 2pg x788, 3pg x5.
- Optional sections are present at realistic rates (e.g. `about` 73%,
  `projects` 64%, `certificates` 39%,
  `hobbies` 35%).

### Roles (top 12)

| Role | Count |
| --- | --- |
| System Administrator | 48 |
| Support Specialist | 41 |
| Networking Specialist | 38 |
| Data Scientist | 37 |
| Mobile Developer(IOS/Android) | 37 |
| Scrum Master | 36 |
| Security Specialist | 34 |
| Developer | 34 |
| DB Administrator | 34 |
| Architect | 34 |
| Product Owner | 34 |
| Machine Learning Engineer | 34 |

### Languages

| Language | Resumes |
| --- | --- |
| English | 1000 |
| Hebrew | 271 |
| Uzbek | 265 |
| Spanish | 265 |
| Russian | 259 |
| German | 253 |
| French | 232 |

## Limitations

- **Scope:** all 1000 planned samples are included.
- **Domain:** IT / software-industry roles only; prose is in English.
- A small number of given-name repeats exist among the first 25 samples (generated before a
  name-diversity safeguard was added); later samples are de-clustered.
- Phone numbers use a single fictional format; date and country surface forms follow the
  generator's conventions. See the datasheet for the full list.

## License & citation

Released under **CC-BY-4.0**. If you use this dataset, please cite it and link back to this repo
and the companion model `sukhrobnurali/qwen3vl-resume-parser`.

See [`DATASHEET.md`](DATASHEET.md) for the full datasheet (Gebru et al.).