Document Intelligence Pipelines
Document intelligence converts source structure, meaning, and review history into operational data—not text extraction alone.
Preserve layouts, tables, forms, and signatures across HWP, HWPX, PDF, and images while linking extraction, validation, and approval.
01
Problem definition
Flat text conversion destroys merged cells, paragraph hierarchy, and annotations, misleading downstream automation.
When extraction errors pass silently, reviewers cannot reconcile results with source material.
- Document structure matters to decisions, validation, or downstream systems
- Lineage and human approval must connect source to extracted fields
- Inputs are already trustworthy structured data
- No owner can retain sources and review errors
Document Intelligence Pipelines: system plate
- 01
Stage 1
Detect format, version, encryption, and corruption while fixing a source hash.
- 02
Stage 2
Transform paragraphs, tables, and objects into an intermediate representation preserving layout and reading order.
- 03
Stage 3
Connect rule and model extraction to field schemas, confidence, and source coordinates.
- 04
Stage 4
Route high-risk or low-confidence fields to human review and retain corrections as learnable evidence.
- The workflow begins with Detect format, version, encryption, and corruption while fixing a source hash..
- It reaches an acceptance decision through Structure and field accuracy.
03
Design method
Document intelligence converts source structure, meaning, and review history into operational data—not text extraction alone.
- 01
Stage 1
Detect format, version, encryption, and corruption while fixing a source hash.
- 02
Stage 2
Transform paragraphs, tables, and objects into an intermediate representation preserving layout and reading order.
- 03
Stage 3
Connect rule and model extraction to field schemas, confidence, and source coordinates.
- 04
Stage 4
Route high-risk or low-confidence fields to human review and retain corrections as learnable evidence.
04
Application scenarios
Document structure matters to decisions, validation, or downstream systems
Flat text conversion destroys merged cells, paragraph hierarchy, and annotations, misleading downstream automation.
- APPROACH
- Detect format, version, encryption, and corruption while fixing a source hash.
- BOUNDARY
- Format support is not claimed as complete interpretation of every template.
Lineage and human approval must connect source to extracted fields
When extraction errors pass silently, reviewers cannot reconcile results with source material.
- APPROACH
- Transform paragraphs, tables, and objects into an intermediate representation preserving layout and reading order.
- BOUNDARY
- Confidence alone does not auto-approve high-risk fields.
05
Design choices
| Decision | Gain | Cost | Watch |
|---|---|---|---|
| Document structure matters to decisions, validation, or downstream systems | Detect format, version, encryption, and corruption while fixing a source hash. | Format support is not claimed as complete interpretation of every template. | Structure and field accuracy |
| Lineage and human approval must connect source to extracted fields | Transform paragraphs, tables, and objects into an intermediate representation preserving layout and reading order. | Confidence alone does not auto-approve high-risk fields. | Source-evidence traceability |
Document Intelligence Pipelines: system plate
- Flat text conversion destroys merged cells, paragraph hierarchy, and annotations, misleading downstream automation.
- Format support is not claimed as complete interpretation of every template.
- Transform paragraphs, tables, and objects into an intermediate representation preserving layout and reading order.
- Structure and field accuracy
- Review load and post-correction error rate
- Confidence alone does not auto-approve high-risk fields.
- The workflow begins with Detect format, version, encryption, and corruption while fixing a source hash..
- It reaches an acceptance decision through Structure and field accuracy.
07
Validation plan
| Measure | Method | Pass condition | Caveat |
|---|---|---|---|
| Structure and field accuracy | Detect format, version, encryption, and corruption while fixing a source hash. | Repeated runs satisfy the acceptance threshold agreed during discovery | Format support is not claimed as complete interpretation of every template. |
| Source-evidence traceability | Transform paragraphs, tables, and objects into an intermediate representation preserving layout and reading order. | Repeated runs satisfy the acceptance threshold agreed during discovery | — |
| Review load and post-correction error rate | Connect rule and model extraction to field schemas, confidence, and source coordinates. | Repeated runs satisfy the acceptance threshold agreed during discovery | — |
08
Constraints and failure conditions
Inputs are already trustworthy structured data
Format support is not claimed as complete interpretation of every template.
No owner can retain sources and review errors
Confidence alone does not auto-approve high-risk fields.
09
Engagement model
- 01
Diagnosis
PattyAnalyze the current system and its failure signals.
ClientProvide representative work, data boundaries, and operating constraints.
Structure and field accuracy - 02
Design
PattyTransform paragraphs, tables, and objects into an intermediate representation preserving layout and reading order.
ClientConfirm owners and acceptance criteria.
Source-evidence traceability - 03
Validation
PattyConnect rule and model extraction to field schemas, confidence, and source coordinates.
ClientMake the production-transition or stop decision.
Review load and post-correction error rate
10
Durable deliverables
- Document Intelligence Pipelines decision record
- Document intelligence converts source structure, meaning, and review history into operational data—not text extraction alone.Client-owned · Patty-reviewed
- Validation harness and acceptance criteria
- Structure and field accuracy · Source-evidence traceability · Review load and post-correction error rateJointly maintained
- Operations and recovery runbook
- Format support is not claimed as complete interpretation of every template. · Confidence alone does not auto-approve high-risk fields.Operating-team owned
11
Terminology
- Document Intelligence Pipelines
- Preserve layouts, tables, forms, and signatures across HWP, HWPX, PDF, and images while linking extraction, validation, and approval.
- Acceptance criterion
- Structure and field accuracy
- Operating boundary
- Format support is not claimed as complete interpretation of every template.
REFERENCES
References and primary material
- HWPX OWPML specification
Primary material for the method and terminology.
- LayoutLMv3
Primary material for the method and terminology.