Algorithmic Entity Resolution in Music Metadata

In the global streaming economy, Spotify, Apple Music, and other DSPs process billions of plays daily. Behind this massive transaction layer lies a fragmented, dual-copyright structure: The Recording Copyright (Master Right): Identifies the audio file, registered using the ISRC (International Standard Recording Code). The Composition Copyright (Publishing Right): Identifies the melody, lyrics, and arrangement, registered using the ISWC (International Standard Musical Work Code). Because these registries are managed by separate global entities (IFPI for ISRCs and CISAC for ISWCs), there is no central mapping registry between them. This gap causes millions of dollars in mechanical royalties to sit unclaimed in collective management organization (CMO) "Black Boxes" before being liquidated to major publishers. In this article, we'll design and implement a high-performance Semantic Entity Resolution Protocol (SERP) to bridge this metadata gap programmatically. The SERP Resolution Pipeline Reconciling these records requires a multi-layered classification pipeline. Since manual matching is logistically impossible, we implement a three-tiered algorithmic approach: ┌────────────────────────┐ │ Raw Recording & Work │ │ Data Ingestion │ └───────────┬────────────┘ │ ▼ ┌────────────────────────┐ │ 1. Normalized Title │ ──[Similarity < 0.85]──> [Unmatched Queue] │ Distance Filter │ └───────────┬────────────┘ │ [Similarity >= 0.85] ▼ ┌────────────────────────┐ │ 2. Creator Overlap │ ──[No Overlap]──────────> [Unmatched Queue] │ Intersection Matrix │ └───────────┬────────────┘ │ [Intersection >= 1] ▼ ┌────────────────────────┐ │ 3. Duration Tolerance │ ──[Delta > 4s]──────────> [Manual Verification] │ Guard Check │ └───────────┬────────────┘ │ [Delta <= 4s] ▼ ┌────────────────────────┐ │ Verified Link & │ │ CMO Dispute Ready │ └────────────────────────┘ Step 1: Normalization & String Similarity Filter Title comparisons often fail due to punctuation mismatches, subtitle variations,