chore(8.0): final pre-RC1 sweep — API consistency, named errors, orphans, zero-cast codebase

src/neural/entityExtractor.ts

@@ -3,7 +3,7 @@
  * Uses embeddings and similarity matching for accurate type detection
  *
  * Now powered by SmartExtractor for ultra-neural classification
- * PRODUCTION-READY with caching support
+ * Entity extraction with caching support
  */
 
 import { NounType } from '../types/graphTypes.js'
@@ -293,8 +293,8 @@ export class NeuralEntityExtractor {
     const contextLower = context.toLowerCase()
     let boost = 0
     
-    // Context clues for each type
-    const contextClues: Record<NounType, string[]> = {
+    // Context clues for each type (partial: only types with known clue words)
+    const contextClues: Partial<Record<NounType, string[]>> = {
       [NounType.Person]: ['mr', 'ms', 'mrs', 'dr', 'prof', 'said', 'told', 'wrote'],
       [NounType.Organization]: ['inc', 'corp', 'llc', 'ltd', 'company', 'announced'],
       [NounType.Location]: ['in', 'at', 'from', 'to', 'near', 'located', 'city', 'country'],
@@ -304,7 +304,7 @@ export class NeuralEntityExtractor {
       [NounType.Currency]: ['$', '€', '£', '¥', 'usd', 'eur', 'price', 'cost'],
       [NounType.Message]: ['email', 'message', 'sent', 'received', 'wrote', 'reply'],
       // Add more context clues as needed
-    } as any
+    }
     
     const clues = contextClues[type] || []
     for (const clue of clues) {
@@ -401,8 +401,8 @@ export class NeuralEntityExtractor {
     this.embeddingCacheStats.misses++
 
     let vector: Vector
-    if ('embed' in this.brain && typeof (this.brain as any).embed === 'function') {
-      vector = await (this.brain as any).embed(text)
+    if ('embed' in this.brain && typeof this.brain.embed === 'function') {
+      vector = await this.brain.embed(text)
     } else {
       // Fallback - create simple hash-based vector
       vector = new Array(384).fill(0)