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Symio-ai/legal-statute-parser

sourceHugging Faceapache-2.0updated 6mo agoView on Hugging Face
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Model Card

Symio-ai/legal-statute-parser

Model Description

Legal Statute Parser performs structured extraction from statute text. Given raw statute text, it identifies and labels: section numbers, subsections, definitions, operative clauses, penalty provisions, exceptions, effective dates, amendment history, and cross-references.

Designed to power the GLACIER pipeline's statute verification and element-mapping stages.

Intended Use

  • —Primary: Parse statute text into structured components for element mapping
  • —Secondary: Identify penalty ranges, damage caps, and procedural requirements from statute text
  • —Integration: Feeds into legal-element-mapper and legal-damages-calculator models

Task Type

token-classification -- Named entity recognition for statutory components

Base Model

nlpaueb/legal-bert-base-uncased -- Pre-trained on legal corpora (EU legislation, US court opinions, contracts), strong baseline for legal NER tasks

Training Data

SourceRecordsDescription
US Code (all titles)~60K sectionsFull federal statutory text with structure labels
Florida Statutes~12K sectionsF.S. chapters relevant to litigation (chs. 768, 95, 92, 48, etc.)
Mississippi Code~8K sectionsMS Code sections for active jurisdictions
State Legislature Archives~200K sectionsHistorical versions for amendment tracking

Entity Labels

  • —SECTION_NUM -- Statute section identifier (e.g., 768.72)
  • —SUBSECTION -- Subsection reference (e.g., (1)(a))
  • —DEFINITION -- Defined term and its definition text
  • —OPERATIVE -- The core operative language ("shall", "must", "is liable")
  • —PENALTY -- Penalty or damages provision
  • —EXCEPTION -- Exception or exclusion clause
  • —EFFECTIVE_DATE -- Effective date of provision
  • —XREF -- Cross-reference to another statute
  • —ELEMENT -- Required element for a cause of action

Benchmark Criteria (90%+ Target)

MetricTargetDescription
Entity F1>= 92%Macro F1 across all entity types
ELEMENT Recall>= 95%Must capture all cause-of-action elements
PENALTY Precision>= 93%Penalty provisions must be correctly identified
XREF Accuracy>= 90%Cross-references must resolve correctly
Latency< 500msPer-section parse time

GLACIER Pipeline Integration

STAGE 2 (Research) --> statute-parser extracts elements from relevant statutes
STAGE 3 (WDC #1)  --> parsed elements fed to element-mapper for theory validation
STAGE 4 (Draft)    --> parsed penalty provisions inform damages calculator
STAGE 5 (WDC #2)  --> verify all statute references in draft are current

Training Configuration

  • —Epochs: 10
  • —Learning rate: 3e-5 with cosine schedule
  • —Batch size: 16
  • —Max sequence length: 512
  • —Hardware: AWS SageMaker ml.g5.2xlarge

Limitations

  • —Focused on FL, MS, and federal statutes; other state statutes may have lower accuracy
  • —Archaic statutory language (pre-1970) may parse with lower confidence
  • —Does not perform constitutional analysis or preemption checks
  • —Assumes standard US statutory formatting conventions

Version History

VersionDateNotes
v0.12026-04-10Initial model card, repo created