Legal Data Indexing
The DataHive Legal Data Indexing system is a core component of the LN1 node that processes, categorizes, and indexes legal documents for the decentralized legal intelligence network.
Key Components
Document Processing
- Raw document ingestion
- Text extraction and normalization
- Metadata generation
- Format standardization
Classification Engine
- Legal document type detection
- Jurisdiction identification
- Subject matter categorization
- Precedent relationship mapping
Index Structure
class LegalIndex:
def __init__(self):
self.document_store = DocumentStore()
self.metadata_index = MetadataIndex()
self.citation_graph = CitationGraph()
async def process_document(self, document):
metadata = self.extract_metadata(document)
citations = self.extract_citations(document)
return await self.store(document, metadata, citations)
Indexing Pipeline
Document Collection
- API-based document submission
- Batch processing capabilities
- Version control tracking
- Source verification
Processing Steps
- Document validation
- Content extraction
- Language detection
- Structure analysis
- Document attributes
- Legal classifications
- Temporal information
- Jurisdictional data
Integration Points
Network Interface
- Cross-node synchronization
- Distributed index updates
- Consensus validation
- Version management
Storage Layer
- Integration with 0G AIOS
- Distributed storage protocol
- Content-addressable system
- Redundancy management
Search Capabilities
Query Processing
- Legal term recognition
- Context-aware search
- Precedent matching
- Cross-reference resolution
Results Ranking
- Relevance scoring
- Authority weighting
- Temporal factors
- Jurisdictional priority
Note: This documentation is subject to updates as the indexing system evolves.