Slash Command

/entity-extraction

Extract named entities from legal documents and map relationships using NLP network analysis

npx claudepluginhub jdrodriguez/legal-toolkit --plugin legal-toolkit

Popularity

Parent stars

Invocation

How this command is triggered — by the user, by Claude, or both

Slash command

/legal-toolkit:entity-extraction <file or folder of documents>

Model invocable

No pre-commands

Context Preview

The summary Claude sees in its command listing — used to decide when to auto-load this command

# /entity-extraction -- Entity & Relationship Mapper

Extract named entities (people, organizations, dates, monetary amounts, jurisdictions, legal references) from legal documents and build interactive relationship graphs showing how entities connect across documents.

@$1

Examples:
- `/legal-toolkit:entity-extraction ~/cases/johnson-dui/discovery/`
- `/legal-toolkit:entity-extraction ~/cases/martinez/police-reports/ ~/cases/martinez/witness-statements/`
- `/legal-toolkit:entity-extraction ~/cases/complex-fraud/full-document-set/`

## Workflow

- **Validate** the input path (file or direct...

Command Content

25 lines · ~375 tokens

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Stats

Parent stars2

MaintenanceExcellent

Last CommitMar 11, 2026

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# /entity-extraction -- Entity & Relationship Mapper Extract named entities (people, organizations, dates, monetary amounts, jurisdictions, legal references) from legal documents and build interactive relationship graphs showing how entities connect across documents. @$1 Examples: - `/legal-toolkit:entity-extraction ~/cases/johnson-dui/discovery/` - `/legal-toolkit:entity-extraction ~/cases/martinez/police-reports/ ~/cases/martinez/witness-statements/` - `/legal-toolkit:entity-extraction ~/cases/complex-fraud/full-document-set/` ## Workflow - **Validate** the input path (file or direct...

/entity-extraction -- Entity & Relationship Mapper

Extract named entities (people, organizations, dates, monetary amounts, jurisdictions, legal references) from legal documents and build interactive relationship graphs showing how entities connect across documents.

@$1

Examples:

/legal-toolkit:entity-extraction ~/cases/johnson-dui/discovery/

/legal-toolkit:entity-extraction ~/cases/martinez/police-reports/ ~/cases/martinez/witness-statements/

/legal-toolkit:entity-extraction ~/cases/complex-fraud/full-document-set/

Workflow

Validate the input path (file or directory) and check for supported formats (.pdf, .docx, .txt, .md)

Extract entities using the map-entities skill's Python script with spaCy NLP for named entity recognition

Present entity summary: total entities by type (PERSON, ORG, DATE, MONEY, GPE, LAW), most frequent entities, key people, key organizations

Highlight relationships: most connected entities, entity clusters, and cross-document entity appearances

Generate output files: entity_database.xlsx, relationship_graph.html (interactive network), cross_reference_matrix.xlsx, timeline_dates.xlsx, financial_mentions.xlsx

Refer to the map-entities skill (SKILL.md) for NLP model options, minimum mention thresholds, and AI-powered relationship analysis