paperless-classify

name

paperless-classify

description

Use when classifying, triaging, or organizing Paperless documents; reviewing the paperless inbox; assigning document metadata; discussing taxonomy conventions; or running `./scripts/paperless.sh classify`. Triggers on phrases like "classify documents", "triage paperless", "check the inbox", "what needs classification", "paperless taxonomy". Do NOT use for uploading documents, managing users/groups/workflows, or general paperless CRUD.

Paperless Document Classification

Classify documents in Paperless-ngx by analyzing OCR content and assigning metadata (correspondent, document type, tags, title) using existing taxonomy. The LLM is the classifier; the CLI provides the data gathering and persistence interface.

Prerequisites

• "inbox" tag exists with is_inbox_tag=true (created automatically by ensure_inbox_tag())
• A Paperless workflow assigns the inbox tag to all newly consumed documents
• Taxonomy (types, correspondents, tags) is populated with initial entries
• Documents have been uploaded and OCR processing is complete

Discovery

Run --help on relevant subcommands before the first classification session. Key capabilities to know about:

• correspondent create accepts multiple names: correspondent create "A" "B" "C" (one call)
• bulk tag, bulk set-type, bulk set-correspondent operate on comma-separated doc IDs
• classify apply reads structured input from stdin (see step 4 below)

Workflow

1. Check the inbox

./scripts/paperless.sh classify inbox

Shows documents with the inbox tag. These have not yet been reviewed, regardless of whether Paperless auto-assigned some fields.

2. Get the briefing

# All inbox docs (default limit 10, compact 500 chars)
./scripts/paperless.sh classify brief

# Specific documents
./scripts/paperless.sh classify brief 12 13 14

# Full content (2000 chars + keywords for long docs)
./scripts/paperless.sh classify brief 14 --full

Default output is compact: taxonomy header, per-doc metadata, and the first 500 chars of sanitized content. This is usually enough to classify. For ambiguous documents, re-run with --full on just those doc IDs to get 2000 chars plus YAKE keyword extraction for long documents.

3. Analyze and decide

For each document, determine:

1. Correspondent (who issued it)
2. Document type (what form it takes)
3. Tags (topical domains)
4. Title (clean, normalized)

4. Apply classification

Bulk-classify via classify apply, which reads pipe-delimited lines from stdin:

./scripts/paperless.sh classify apply <<'EOF'
278|18|7|7|W-2 Wage and Tax Statement (2025)
277|19|7|7,3|W-2 Wage and Tax Statement (2025)
248||7|7|W-4 Employee Withholding Certificate (2023)
EOF

Format: id|correspondent_id|type_id|tag_ids|title

• Correspondent and type fields can be empty to skip (preserves existing value)
• Tag IDs are comma-separated within the field; empty means no tags
• The inbox tag is removed automatically
• Lines starting with # and blank lines are ignored
• Errors on individual documents are reported but do not abort the batch

For single-document updates, doc update is still available:

./scripts/paperless.sh doc update ID \
  --title "Clean Title Here" \
  --correspondent CORR_ID \
  --type TYPE_ID \
  --tag TAG_ID --tag TAG_ID

The --tag flag uses replace semantics: specified tags become the complete tag set. The inbox tag is automatically removed on any doc update call, signaling that classification is done.

After applying a batch, re-run classify inbox and inspect any documents that remain. Re-read a sample of updated documents when the command reports an individual failure or unexpected count.

5. Handle taxonomy gaps

If a document needs a correspondent, type, or tag that does not exist:

• Correspondent: Create without asking (each business is unique)
• Tag: Propose to user before creating (tags must earn their existence)
• Type: Propose to user before creating (types are finite; see cap below)

# Multiple correspondents in one call
./scripts/paperless.sh correspondent create "Milliman" "UTA" "Studio Designer"

# Single type or tag
./scripts/paperless.sh tag create "home"
./scripts/paperless.sh type create "Warranty"

Taxonomy Conventions

Document Types (the "what")

The broad form of the document. Finite set, hard cap at 25.

Examples: Receipt, Invoice, Insurance Policy, Warranty, Contract, Tax Return, Bank Statement, Certificate, License, Letter, Manual, Recipe

Principles:

• Types describe the document's form, not its topic
• If two documents would go in the same physical folder type, they share a type
• "Carpet Cleaning Receipt" is wrong; "Receipt" is the type
• Challenge whether an existing type fits before proposing a new one
• If count reaches 26, stop and consolidate immediately (merge + bulk reassign)

Correspondents (the "who")

The entity that issued or produced the document. Normalized to common business name.

Examples: "AAA Insurance" (not "Auto Club Indemnity Company"), "Parker Brothers Carpet Cleaning", "Wells Fargo", "IRS"

Principles:

• Use the name you would say out loud
• Merge subsidiaries into the parent brand you recognize
• One correspondent per entity; no department variants
• NEVER a family member; correspondents are external issuers only
• Create freely (each business is unique)

Tags (the "about")

Topical labels that cut across types and correspondents. Enable cross-domain queries.

Examples: home, auto, medical, pets, financial, technology, school, appliances

Principles:

• Tags must NOT duplicate what type or correspondent already captures
• Tags answer "what domain is this relevant to?" not "what is it?"
• Broad tags that compose well: "home" + type "Warranty" beats a "home-warranty" tag
• Aim for 10-20 total; each should apply to 5+ documents to earn its existence
• Property-specific tags acceptable if filtering by property is useful
• Never create single-use tags

Title Formatting

Paperless displays titles as Correspondent: Title in the UI. Titles MUST NOT repeat the correspondent name; that creates redundant display like TxDMV: TxDMV - Certificate of Title.

• Structure: Description (Date or Context)
• Examples:
  • "Carpet Cleaning Invoice (Oct 2024)"
  • "Home Policy Declaration (2025-2026)"
  • "QX60 Transmission Rebuild Warranty (Nov 2022)"
  • "Certificate of Title, 2016 Mazda 6 (Jul 2016)"
• Keep titles concise but specific enough to distinguish from similar documents
• Include date context when the document is time-bounded
• The correspondent field provides the "who"; the title provides the "what"

Taxonomy Maintenance

Type consolidation (when cap is reached)

# List current types
./scripts/paperless.sh type list

# Identify types to merge, then bulk-update affected docs
./scripts/paperless.sh doc list --type OLD_TYPE_ID
# Update each doc to new type, then delete the old type
./scripts/paperless.sh type delete OLD_TYPE_ID

Reviewing auto-classification

Paperless auto-classifies on ingestion using a sklearn classifier trained on existing documents. Its assignments may be wrong. The inbox workflow reviews ALL documents that still carry the inbox tag, regardless of whether Paperless pre-filled fields. When the brief shows incorrect auto-assigned values, overwrite them with correct values.

Over time, correct classifications improve the auto-classifier. The feedback loop is automatic.

Decision Framework

Action	When	Ask user?
Create correspondent	Always (each business is unique)	No
Create tag	No existing tag covers the domain	Yes
Create type	No existing type fits the form	Yes
Merge types	Count reaches 26	Yes (confirm plan)
Delete tag/type	Never without explicit request	Always

Content Strategy

The brief command applies these transformations to document content:

1. Fix encoding artifacts (ftfy)
2. Strip fill characters, decorative separators, excess whitespace
3. Truncate to first 500 characters (compact, default) or 2000 characters (--full)
4. Append YAKE keyword extraction for documents over 5000 characters (--full only)

Use the two-pass approach: compact brief for the full batch, then --full for just the ambiguous docs. For complete untruncated content, use doc show ID --full.