Published by Sejong AI Research Center · Independent research insightsSource review 2026-11-05 KST
SEJONG AI · INSIGHTKorean Document AI Review
한국어Discuss local LLM
SEJONG AI INSIGHT Korean Document AI Review

HWP · HWPX · MACHINE-READABLE DOCUMENTS

From Korean documents
to usable AI knowledge.

Understand HWP and HWPX, conversion limits, tables and layout checks through practical document workflows.

Read the briefs ↓Local LLM consultation ↗

After changing the extension, check tables, notes and layout against the task your documents need to support.

HWP vs HWPXKorean document AIpublic document conversion
REVIEW NOTE

Includes reporting on the 3 November cabinet discussion. Format support and structural understanding require separate checks.

View evidence →
BRIEFING & SOURCES

Briefs grounded in sources

REVIEWED 2026-11-05

FROM EVIDENCE TO PRACTICE

What should a conversion review cover?

01

Preserve originals

Keep provenance, versions and permissions with the source.

02

Extract structure

Compare table rows, columns, notes and figures as well as text.

03

Validate the task

Check omissions in search, answers and form editing.

Practice questions · Proposed by the research center
  • Preserve relationships in merged table cells
  • Distinguish footnotes, headers and footers
  • Identify scanned images separately from text
  • Link every extracted claim back to its source page
REFERENCE ARCHITECTURE / PROPOSED SCOPE

Beyond a model. Toward a system you can evaluate.

SYSTEM DESIGN / 01—07

A reference scope for evaluating an institutional local LLM project. Actual delivery, performance and acceptance conditions depend on the institution’s documents, security environment and agreed requirements. These items do not claim a completed deployment or certification.

INTERACTIVE REFERENCE / 01—07

Select an area to explore its scope and review criteria.

REFERENCE MODULE
02

Korean document structure

Evaluate relationships between text, tables, notes and images using representative administrative documents.

  • Comparison samples for merged cells, columns and notes
  • Identification of OCR needs and extraction omissions
  • Evidence links back to source pages or sections
View the complete module checklist
02HWPX STRUCTURE

Korean document structure

Evaluate relationships between text, tables, notes and images using representative administrative documents.

  • Comparison samples for merged cells, columns and notes
  • Identification of OCR needs and extraction omissions
  • Evidence links back to source pages or sections
01DOCUMENT INTAKE

Document intake and provenance

Design a document path that connects originals, versions and processing history to each answer.

  • Rules for supported, encrypted and damaged files
  • Original retention, deduplication and version identity
  • Failure records and controlled reprocessing
05EVIDENCE EVALUATION

Quality tested against real work

Define how to assess evidence accuracy, omissions, wrong answers and human correction effort.

  • Agreed documents, questions and reference answers
  • Separate records of retrieval and generation failures
  • Deferral or clarification when evidence is insufficient
03GOVERNED RETRIEVAL

Permission-aware retrieval

Define how document access rights carry through indexing and retrieval results.

  • Mapping users, departments and document permissions
  • Checks after access changes or revocation
  • Links between answer evidence and document versions
04LOCAL INFERENCE

Inference for institutional infrastructure

Review models, hardware, concurrent use and external connections as a single operating scenario.

  • Model terms, import checks and update procedures
  • Methods for measuring task latency and concurrent use
  • An inventory of external API and telemetry paths
06OPERATIONS & AUDIT

Observable operations and accountability

Define logging, correction and incident-response boundaries and owners before adoption.

  • Log fields, sensitive-data handling and retention
  • An owned path from error reports to corrections
  • Recorded incident, backup and recovery checks
07DELIVERY & ACCESS

Delivery, handover and accessibility

Plan the handover needed to verify, change and operate the system after installation.

  • Installation, environment and operations documentation
  • Approval, release and rollback procedures
  • Keyboard, zoom, contrast and reduced-motion checks
DELIVERY FRAMEWORK

From an idea to acceptance and operation.

REFERENCE DELIVERY PLAN
01 / DEFINE

Define the task and boundaries

Identify users, documents, permissions and data paths, then select the priority workflow.

Requirements, data flows and evaluation plan
02 / PROVE

Prove the approach with samples

Evaluate extraction, retrieval and answers separately and document their limits.

Sample results, issues and improvement priorities
03 / INTEGRATE

Integrate access and operations

Connect permissions, logs, approvals and error handling in the agreed environment.

Integrated configuration, procedures and acceptance scenarios
04 / TRANSFER

Accept and transfer operations

Review acceptance evidence and agree training, documentation and ongoing support.

Acceptance records, handover package and ownership matrix

Acceptance should rest on reproducible evidence.

  • Can the agreed documents, questions and test environment be rerun?
  • Have document-level access changes and revocation been checked?
  • Are source evidence and error-handling records retained?
  • Have release, recovery and operations documents and owners been handed over?
QUESTIONS & ANSWERS

About this resource

Is this an official K-Moonshot website?

An independent private information and analysis service by Sejong AI Research Center. Not a government website or the official operator of K-Moonshot. Facts, media reports and our analysis are labeled separately.

Will a new article appear every day?

We aim to review sources daily. Briefs are added or corrected when a verified substantive development warrants it. No-news days do not generate filler articles, and the displayed review date follows actual source checks.

Where do consultation links go?

They lead to the existing Sejong AI Research Center contact page at SEJONG-AI.COM. This information site does not collect inquiry details or documents.

LOCAL LLM · ON-PREMISE

Your documents are in HWPX.
Are they ready for the task?

For documents with important tables, notes or forms, assess format support and task quality separately. Describe the format and workflow to discuss a local LLM approach.

Tell us whether search, summarization or drafting is the priority.
Prepare your inquiry

We are evaluating AI workflows using tables, notes and forms in HWP/HWPX documents. Our document scope is [scope], priority task is [search/summarization/drafting], and environment is [environment]. We would like to discuss sample evaluation and a local LLM architecture.

Discuss document AI ↗SEJONG-AI.COM
INSIGHT NETWORK

Explore a related subject

One research center, five distinct perspectives

01 / POLICYK-Moonshot Policy Observatoryk-moonshot.com ↗02 / DOCUMENTKorean Document AI Reviewk-moonshot.co.kr ↗03 / LOCAL LLMLocal LLM Practice Notesk-moonshot.kr ↗04 / GOVERNANCEPublic AI Governance Deskkmoonshot.co.kr ↗05 / GLOBALKorea AI & Sovereignty Briefkmoonshot.kr ↗