Symio-ai/legal-entity-resolver

Symio-ai/legal-entity-resolver

Model Description

Legal Entity Resolver identifies, disambiguates, and links entities across legal documents. It resolves party name variations (e.g., "ABC Corp", "ABC Corporation", "A.B.C. Corp., Inc."), identifies alter ego relationships, maps corporate hierarchies, and links individuals to their various roles (officer, director, agent, trustee).

Critical for ensuring correct party identification in multi-party litigation and corporate veil-piercing analysis.

Intended Use

• —Primary: Resolve entity references across case documents to maintain consistent party identification
• —Secondary: Identify corporate relationships for alter ego and veil-piercing analysis
• —Integration: Entity resolution layer used across all GLACIER pipeline stages

Task Type

token-classification -- Named entity recognition with entity linking and coreference resolution

Base Model

microsoft/deberta-v3-large -- Strong NLI and token classification for entity disambiguation

Training Data

Entity Types

• —PERSON -- Natural person (with name variations)
• —CORPORATION -- Corporate entity (with DBA, trade names)
• —LLC -- Limited liability company
• —PARTNERSHIP -- General or limited partnership
• —TRUST -- Trust entity
• —GOVERNMENT -- Government agency or official (in official capacity)
• —ROLE -- Individual's role (officer, director, agent, registered agent)
• —ALTER_EGO -- Entity identified as alter ego of another

Resolution Output

{
  "resolved_entities": [
    {
      "canonical_name": "ABC Corporation, Inc.",
      "variations_found": ["ABC Corp", "A.B.C. Corp., Inc.", "ABC"],
      "type": "CORPORATION",
      "state_registration": "FL Sunbiz #P12345678",
      "officers": ["John Smith (CEO)", "Jane Doe (Secretary)"],
      "related_entities": [
        {"name": "XYZ LLC", "relationship": "subsidiary", "ownership": "100%"}
      ],
      "alter_ego_indicators": ["shared address", "commingled funds", "undercapitalized"]
    }
  ]
}

Benchmark Criteria (90%+ Target)

GLACIER Pipeline Integration

STAGE 1 (Classify) --> entity-resolver identifies all parties in the case
STAGE 2 (Research) --> resolver disambiguates party names in research results
STAGE 4 (Draft) --> resolver ensures consistent party naming in filings
STAGE 5 (WDC #2) --> verify all party references are consistent and correct

Training Configuration

• —Epochs: 8
• —Learning rate: 2e-5
• —Batch size: 16
• —Max sequence length: 512
• —Hardware: AWS SageMaker ml.g5.4xlarge

Limitations

• —Extremely common names (e.g., "John Smith") are harder to disambiguate without context
• —Dissolved or historical entities may not appear in current registration databases
• —International entities have limited coverage
• —Informal entity references (nicknames, abbreviations) may not resolve without context
• —Does not perform skip-tracing or locate individuals (see people-finder MCP for that)

Version History