Skip to content

Repository files navigation

LI-ESKG

Paper | GitHub

LI-ESKG integrates uncertain entity resolution with an authoritative event-state knowledge graph. The implementation separates three planes:

  • an active, allocation-reusing probabilistic workspace;
  • an append-only resolution ledger containing immutable evidence, inference, decisions, revisions, dependencies, outbox entries, and receipts;
  • a host-only graph containing accepted native event-state relations.

Python

The typed licorne extension exposes V2 observations, collective inference, dynamic client-defined candidate/factor providers, the hot workspace and storage contracts, host-graph materialization, standards projection, and a bounded asynchronous resolver. Its pooled single-tenant scheduler keeps one ledger and logical runtime per tenant while sharing only scrubbed workspace allocations and a fixed execution-thread set. H3 is available only as an optional provider index; it has no role in default resolution semantics.

See the Python guide for installation and an asynchronous create-then-match example.

Benchmarks

Benchmarked on a M2 Apple chip.

Benchmark Scale Execution Time Throughput
Observation Partition 500,000 obs 69.8 ms 7.16 Melem/s
Identity Uniqueness 400,000 nodes 2.30 ms 173.77 Melem/s
Causal Acyclicity 300,000 rels 3.95 ms 76.05 Melem/s
Batch Insertion 1,000,000 items 76.4 µs 13.09 Gelem/s
Active Belief Query 1,000,000 items 4.37 ms 228.78 Melem/s
Runtime Pipeline 10,000x10 167 ms 598.8 Kelem/s

About

An implementation of the Latent Identity Event-State Knowledge Graph (LI-ESKG) architecture.

Resources

Stars

0 stars

Watchers

0 watching

Forks

Contributors

Languages