feat: array-unnest groupBy for aggregates + batch-embed entity extraction

- groupBy now supports { field, unnest: true }: an entity contributes once per
  distinct element of an array field (tag frequency / faceted counts). Duplicate
  elements on one entity count once; an empty/missing array joins no group. The
  incremental add/update/delete paths fan out across the unnested groups.
- extractEntities/extractConcepts batch-embed the unique candidate spans in one
  embedBatch call instead of one embed() per candidate (N sequential model calls);
  falls back to per-candidate embedding if the batch fails. No behavior change.

src/neural/signals/EmbeddingSignal.ts

@@ -151,6 +151,8 @@ export class EmbeddingSignal {
       definition?: string
       allTerms?: string[]
       metadata?: any
+      /** Pre-computed candidate embedding (from a batch embed) — skips the per-candidate embed. */
+      vector?: Vector
     }
   ): Promise<TypeSignal | null> {
     this.stats.calls++
@@ -167,8 +169,8 @@ export class EmbeddingSignal {
     }
 
     try {
-      // Embed candidate once (efficiency!)
-      const vector = await this.embedWithTimeout(candidate)
+      // Use the pre-computed vector when the caller batch-embedded; otherwise embed once here.
+      const vector = context?.vector ?? await this.embedWithTimeout(candidate)
 
       // Check all three sources in parallel
       const [typeMatch, graphMatch, historyMatch] = await Promise.all([