diff --git a/web/src/engine/predictive-text/worker-thread/src/main/correction/context-token.ts b/web/src/engine/predictive-text/worker-thread/src/main/correction/context-token.ts
index 5e1cf528681..1e6d32cf2ad 100644
--- a/web/src/engine/predictive-text/worker-thread/src/main/correction/context-token.ts
+++ b/web/src/engine/predictive-text/worker-thread/src/main/correction/context-token.ts
@@ -15,6 +15,7 @@ import { SearchQuotientNode, PathInputProperties } from "./search-quotient-node.
 import { TokenSplitMap } from "./context-tokenization.js";
 import { LegacyQuotientSpur } from "./legacy-quotient-spur.js";
 import { LegacyQuotientRoot } from "./legacy-quotient-root.js";
+import { generateSubsetId } from './tokenization-subsets.js';
 
 import Distribution = LexicalModelTypes.Distribution;
 import LexicalModel = LexicalModelTypes.LexicalModel;
@@ -113,7 +114,8 @@ export class ContextToken {
             start: 0,
             transitionId: undefined
           },
-          bestProbFromSet: BASE_PROBABILITY
+          bestProbFromSet: BASE_PROBABILITY,
+          subsetId: generateSubsetId()
         };
         searchModule = new LegacyQuotientSpur(searchModule, [{sample: transform, p: BASE_PROBABILITY}], inputMetadata);
       });
@@ -313,11 +315,11 @@ export class ContextToken {
         constructingToken = new ContextToken(lexicalModel);
         backupToken = new ContextToken(constructingToken);
         constructingToken.addInput({
+          ...priorSourceInput,
           segment: {
             ...priorSourceInput.segment,
             start: priorSourceInput.segment.start + extraCharsAdded
-          },
-          bestProbFromSet: priorSourceInput.bestProbFromSet
+          }
         }, tailDistribution);
 
         const lenToCommit = lenBeforeLastApply + extraCharsAdded;
diff --git a/web/src/engine/predictive-text/worker-thread/src/main/correction/context-tokenization.ts b/web/src/engine/predictive-text/worker-thread/src/main/correction/context-tokenization.ts
index 20c95b1ecc2..2cdb7d7020b 100644
--- a/web/src/engine/predictive-text/worker-thread/src/main/correction/context-tokenization.ts
+++ b/web/src/engine/predictive-text/worker-thread/src/main/correction/context-tokenization.ts
@@ -591,7 +591,8 @@ export class ContextTokenization {
           transitionId: sourceInput.id,
           start: appliedLength
         },
-        bestProbFromSet: bestProbFromSet
+        bestProbFromSet: bestProbFromSet,
+        subsetId: pendingTokenization.inputSubsetId
       }, distribution);
       appliedLength += KMWString.length(distribution[0].sample.insert);
 
diff --git a/web/src/engine/predictive-text/worker-thread/src/main/correction/search-quotient-node.ts b/web/src/engine/predictive-text/worker-thread/src/main/correction/search-quotient-node.ts
index cf6b2198d58..9df43e9e9a6 100644
--- a/web/src/engine/predictive-text/worker-thread/src/main/correction/search-quotient-node.ts
+++ b/web/src/engine/predictive-text/worker-thread/src/main/correction/search-quotient-node.ts
@@ -78,6 +78,17 @@ export interface PathInputProperties {
    * input is included within the SearchSpace's correction space.
    */
   bestProbFromSet: number;
+
+  /**
+   * A unique identifier noting membership in a specific set of input possibilities with
+   * sufficiently similar properties that all correspond to the same "input segment".
+   *
+   * This tends to serve as an identifying factor for tokenized input distributions,
+   * indicating the distributions were all sourced from the same original input event.
+   *
+   * @see PendingTokenization.inputSubsetId
+   */
+  subsetId: number;
 }
 
 /**
diff --git a/web/src/engine/predictive-text/worker-thread/src/main/correction/search-quotient-spur.ts b/web/src/engine/predictive-text/worker-thread/src/main/correction/search-quotient-spur.ts
index 1dccb58c543..dd36c13490d 100644
--- a/web/src/engine/predictive-text/worker-thread/src/main/correction/search-quotient-spur.ts
+++ b/web/src/engine/predictive-text/worker-thread/src/main/correction/search-quotient-spur.ts
@@ -13,6 +13,7 @@ import { LexicalModelTypes } from '@keymanapp/common-types';
 
 import { EDIT_DISTANCE_COST_SCALE, SearchNode, SearchResult } from './distance-modeler.js';
 import { generateSpaceSeed, PathResult, SearchQuotientNode, PathInputProperties } from './search-quotient-node.js';
+import { generateSubsetId } from './tokenization-subsets.js';
 
 import Distribution = LexicalModelTypes.Distribution;
 import ProbabilityMass = LexicalModelTypes.ProbabilityMass;
@@ -74,7 +75,8 @@ export abstract class SearchQuotientSpur implements SearchQuotientNode {
           transitionId: keystroke.sample.id,
           start: 0
         },
-        bestProbFromSet: keystroke.p
+        bestProbFromSet: keystroke.p,
+        subsetId: generateSubsetId()
       }
     };
     const inputSrc = inputSource as PathInputProperties;
diff --git a/web/src/engine/predictive-text/worker-thread/src/main/correction/tokenization-subsets.ts b/web/src/engine/predictive-text/worker-thread/src/main/correction/tokenization-subsets.ts
index d7cab30e463..27c505f3539 100644
--- a/web/src/engine/predictive-text/worker-thread/src/main/correction/tokenization-subsets.ts
+++ b/web/src/engine/predictive-text/worker-thread/src/main/correction/tokenization-subsets.ts
@@ -7,17 +7,38 @@ import { ContextTokenization, TokenizationEdgeAlignment, TokenizationTransitionE
 import Distribution = LexicalModelTypes.Distribution;
 import Transform = LexicalModelTypes.Transform;
 
+let SUBSET_ID_SEED = 0;
+
+export function generateSubsetId() {
+  return SUBSET_ID_SEED++;
+}
+
 export interface PendingTokenization {
   /**
    * The edge window corresponding to the common tokenization for the subset's inputs
    */
   alignment: TokenizationEdgeAlignment,
+
   /**
    * A set of incoming keystrokes with compatible effects when applied.
    *
    * If passed to `subsetByInterval`, the transforms should result in a single subset.
    */
   inputs: Distribution<Map<number, Transform>>
+
+  /**
+   * A unique identifier associated with this PendingTokenization and its
+   * transforms within `SearchSpace`s.  This ID assists with detecting when
+   * split transforms are re-merged during SearchSpace merges.  Only
+   * input-sources with matching subset ID come from the same subset, and thus
+   * only they should be candidates for re-merging a previous split.
+   *
+   * The subset ID does not necessarily match the transition ID; in fact, there
+   * may be a one-to-many relationship between transition ID and
+   * `inputSubsetId`.  Note that the original transition ID may be found within
+   * each `Transform` value entry found within the `.inputs` map if desired.
+   */
+  inputSubsetId: number;
 }
 
 /**
@@ -134,7 +155,7 @@ export function precomputationSubsetKeyer(tokenizationEdits: TokenizationTransit
   // in this tokenization, but that doesn't matter here - we want to imply the
   // represented keystroke range.
   const boundaryEdgeIndex = editBoundary.tokenIndex - edgeWindow.sliceIndex;
-  const boundaryComponent = `B${editBoundary.tokenIndex}=${editBoundary.sourceRangeKey}`;
+  const boundaryComponent = `B${editBoundary.tokenIndex}=${editBoundary.sourceRangeKey}`; // source range is part of it
 
   components.push(boundaryComponent);
 
@@ -155,7 +176,7 @@ export function precomputationSubsetKeyer(tokenizationEdits: TokenizationTransit
   for(const {0: relativeIndex, 1: transform} of tokenizedTransform.entries()) {
     const insertLen = KMWString.length(transform.insert);
     if(relativeIndex > 0) {
-      // The true boundary lie before the insert if the value is non-zero;
+      // The true boundary lies before the insert if the value is non-zero;
       // don't differentiate here!
       boundaryTextLen = 0;
     }
@@ -188,16 +209,29 @@ export class TokenizationSubsetBuilder {
     const key = this.keyer(precomputation);
 
     // Should file the object and its transform data appropriately.
+    //
+    // Maps any number of Tokenizations and their incoming alignment data to a common key
+    // for final tokenization forms.
     const entry: TokenizationSubset = this._subsets.get(key) ?? {
       pendingSet: new Map(),
       key: key
     }
-    const forTokenization = entry.pendingSet.get(tokenization) ?? {
+
+    // Finds any previously-accumulated data corresponding to both the incoming and
+    // target final tokenization form, creating an empty entry if none yet exists.
+    const forTokenization: PendingTokenization = entry.pendingSet.get(tokenization) ?? {
       alignment: precomputation.alignment,
-      inputs: []
+      inputs: [],
+      inputSubsetId: generateSubsetId()
     };
+
+    // Adds the incoming tokenized transform data for the pairing...
     forTokenization.inputs.push({sample: precomputation.tokenizedTransform, p});
+    // and ensures that the pairing's data-accumulator is in the map.
     entry.pendingSet.set(tokenization, forTokenization);
+
+    // Also ensures that the target tokenization's data (accumulating the pairings)
+    // is made available within the top-level map.
     this._subsets.set(key, entry);
   }
 
diff --git a/web/src/test/auto/headless/engine/predictive-text/worker-thread/context/context-token.tests.ts b/web/src/test/auto/headless/engine/predictive-text/worker-thread/context/context-token.tests.ts
index 49e17f81c97..e242b79c546 100644
--- a/web/src/test/auto/headless/engine/predictive-text/worker-thread/context/context-token.tests.ts
+++ b/web/src/test/auto/headless/engine/predictive-text/worker-thread/context/context-token.tests.ts
@@ -14,7 +14,7 @@ import { default as defaultBreaker } from '@keymanapp/models-wordbreakers';
 import { jsonFixture } from '@keymanapp/common-test-resources/model-helpers.mjs';
 import { LexicalModelTypes } from '@keymanapp/common-types';
 
-import { ContextToken, correction, getBestMatches, models, preprocessInputSources, quotientPathHasInputs, SearchQuotientSpur } from '@keymanapp/lm-worker/test-index';
+import { ContextToken, correction, generateSubsetId, getBestMatches, models, preprocessInputSources, quotientPathHasInputs, SearchQuotientSpur } from '@keymanapp/lm-worker/test-index';
 
 import Distribution = LexicalModelTypes.Distribution;
 import ExecutionTimer = correction.ExecutionTimer;
@@ -123,6 +123,7 @@ describe('ContextToken', function() {
 
     it("merges three tokens from single previously-split transforms", () => {
       const srcTransform = { insert: "can't", deleteLeft: 0, deleteRight: 0, id: 1 };
+      const srcSubsetId = generateSubsetId();
 
       const token1 = new ContextToken(plainModel);
       const token2 = new ContextToken(plainModel);
@@ -134,7 +135,8 @@ describe('ContextToken', function() {
           transitionId: srcTransform.id,
           start: 0
         },
-        bestProbFromSet: 1
+        bestProbFromSet: 1,
+        subsetId: srcSubsetId
       }, [{sample: {insert: 'can', deleteLeft: 0, deleteRight: 0, id: 1}, p: 1}]);
 
       token2.addInput({
@@ -143,7 +145,8 @@ describe('ContextToken', function() {
           transitionId: srcTransform.id,
           start: 3
         },
-        bestProbFromSet: 1
+        bestProbFromSet: 1,
+        subsetId: srcSubsetId
       }, [{sample: {insert: "'", deleteLeft: 0, deleteRight: 0, id: 1}, p: 1}]);
 
       token3.addInput({
@@ -152,7 +155,8 @@ describe('ContextToken', function() {
           transitionId: srcTransform.id,
           start: 4
         },
-        bestProbFromSet: 1
+        bestProbFromSet: 1,
+        subsetId: srcSubsetId
       }, [{sample: {insert: 't', deleteLeft: 0, deleteRight: 0, id: 1}, p: 1}]);
 
       const merged = ContextToken.merge([token1, token2, token3], plainModel);
@@ -162,7 +166,8 @@ describe('ContextToken', function() {
           trueTransform: srcTransform,
           transitionId: srcTransform.id,
           start: 0
-        }, bestProbFromSet: 1
+        }, bestProbFromSet: 1,
+        subsetId: srcSubsetId
       } ]);
       assert.equal(merged.searchModule.inputCount, 1);
       assert.deepEqual((merged.searchModule as SearchQuotientSpur).lastInput, [{sample: srcTransform, p: 1}]);
@@ -177,6 +182,12 @@ describe('ContextToken', function() {
         { insert: "our", deleteLeft: 0, deleteRight: 0, id: 3 },
         { insert: "grapes", deleteLeft: 0, deleteRight: 0, id: 4 }
       ];
+      const srcSubsetIds = [
+        generateSubsetId(),
+        generateSubsetId(),
+        generateSubsetId(),
+        generateSubsetId()
+      ];
 
       // apples
       const token1 = new ContextToken(plainModel);
@@ -194,7 +205,8 @@ describe('ContextToken', function() {
           transitionId: srcTransforms[0].id,
           start: 0
         },
-        bestProbFromSet: 1
+        bestProbFromSet: 1,
+        subsetId: srcSubsetIds[0]
       }, [{sample: srcTransforms[0], p: 1}]);
       token1.addInput({
         segment: {
@@ -202,7 +214,8 @@ describe('ContextToken', function() {
           transitionId: srcTransforms[1].id,
           start: 0
         },
-        bestProbFromSet: 1
+        bestProbFromSet: 1,
+        subsetId: srcSubsetIds[1]
       }, [{sample: {insert: 's', deleteLeft: 0, deleteRight: 0, id: 2}, p: 1}]);
 
       token2.addInput({
@@ -211,7 +224,8 @@ describe('ContextToken', function() {
           transitionId: srcTransforms[1].id,
           start: 1
         },
-        bestProbFromSet: 1
+        bestProbFromSet: 1,
+        subsetId: srcSubsetIds[1]
       }, [{sample: {insert: "and", deleteLeft: 0, deleteRight: 0, id: 2}, p: 1}]);
 
       token3.addInput({
@@ -220,7 +234,8 @@ describe('ContextToken', function() {
           transitionId: srcTransforms[1].id,
           start: 4
         },
-        bestProbFromSet: 1
+        bestProbFromSet: 1,
+        subsetId: srcSubsetIds[1]
       }, [{sample: {insert: 's', deleteLeft: 0, deleteRight: 0, id: 2}, p: 1}]);
       token3.addInput({
         segment: {
@@ -228,7 +243,8 @@ describe('ContextToken', function() {
           transitionId: srcTransforms[2].id,
           start: 0
         },
-        bestProbFromSet: 1
+        bestProbFromSet: 1,
+        subsetId: srcSubsetIds[2]
       }, [{sample: srcTransforms[2], p: 1}]);
 
       token4.addInput({
@@ -237,7 +253,8 @@ describe('ContextToken', function() {
           transitionId: srcTransforms[3].id,
           start: 0
         },
-        bestProbFromSet: 1
+        bestProbFromSet: 1,
+        subsetId: srcSubsetIds[3]
       }, [{sample: srcTransforms[3], p: 1}]);
 
       const merged = ContextToken.merge(tokensToMerge, plainModel);
@@ -247,7 +264,8 @@ describe('ContextToken', function() {
           trueTransform: t,
           transitionId: t.id,
           start: 0
-        }, bestProbFromSet: 1
+        }, bestProbFromSet: 1,
+        subsetId: srcSubsetIds[i]
       })));
       assert.isTrue(quotientPathHasInputs(
         merged.searchModule,
@@ -264,6 +282,12 @@ describe('ContextToken', function() {
         { insert: toMathematicalSMP("our"), deleteLeft: 0, deleteRight: 0, id: 3 },
         { insert: toMathematicalSMP("grapes"), deleteLeft: 0, deleteRight: 0, id: 4 }
       ];
+      const srcSubsetIds = [
+        generateSubsetId(),
+        generateSubsetId(),
+        generateSubsetId(),
+        generateSubsetId()
+      ];
 
       // apples
       const token1 = new ContextToken(plainModel);
@@ -281,7 +305,8 @@ describe('ContextToken', function() {
           transitionId: srcTransforms[0].id,
           start: 0
         },
-        bestProbFromSet: 1
+        bestProbFromSet: 1,
+        subsetId: srcSubsetIds[0]
       }, [{sample: srcTransforms[0], p: 1}]);
       token1.addInput({
         segment: {
@@ -289,7 +314,8 @@ describe('ContextToken', function() {
           transitionId: srcTransforms[1].id,
           start: 0
         },
-        bestProbFromSet: 1
+        bestProbFromSet: 1,
+        subsetId: srcSubsetIds[1]
       }, [{sample: {insert: toMathematicalSMP('s'), deleteLeft: 0, deleteRight: 0, id: 2}, p: 1}]);
 
       token2.addInput({
@@ -298,7 +324,8 @@ describe('ContextToken', function() {
           transitionId: srcTransforms[1].id,
           start: 1
         },
-        bestProbFromSet: 1
+        bestProbFromSet: 1,
+        subsetId: srcSubsetIds[1]
       }, [{sample: {insert: toMathematicalSMP("and"), deleteLeft: 0, deleteRight: 0, id: 2}, p: 1}]);
 
       token3.addInput({
@@ -307,7 +334,8 @@ describe('ContextToken', function() {
           transitionId: srcTransforms[1].id,
           start: 4
         },
-        bestProbFromSet: 1
+        bestProbFromSet: 1,
+        subsetId: srcSubsetIds[1]
       }, [{sample: {insert: toMathematicalSMP('s'), deleteLeft: 0, deleteRight: 0, id: 2}, p: 1}]);
       token3.addInput({
         segment: {
@@ -315,7 +343,8 @@ describe('ContextToken', function() {
           transitionId: srcTransforms[2].id,
           start: 0
         },
-        bestProbFromSet: 1
+        bestProbFromSet: 1,
+        subsetId: srcSubsetIds[2]
       }, [{sample: srcTransforms[2], p: 1}]);
 
       token4.addInput({
@@ -324,7 +353,8 @@ describe('ContextToken', function() {
           transitionId: srcTransforms[3].id,
           start: 0
         },
-        bestProbFromSet: 1
+        bestProbFromSet: 1,
+        subsetId: srcSubsetIds[3]
       }, [{sample: srcTransforms[3], p: 1}]);
 
       const merged = ContextToken.merge(tokensToMerge, plainModel);
@@ -334,7 +364,8 @@ describe('ContextToken', function() {
           trueTransform: t,
           transitionId: t.id,
           start: 0
-        }, bestProbFromSet: 1
+        }, bestProbFromSet: 1,
+        subsetId: srcSubsetIds[i]
       })));
       assert.isTrue(quotientPathHasInputs(
         merged.searchModule,
@@ -372,7 +403,8 @@ describe('ContextToken', function() {
             trueTransform: keystrokeDistributions[i][0].sample,
             transitionId: keystrokeDistributions[i][0].sample.id,
             start: 0
-          }, bestProbFromSet: .75
+          }, bestProbFromSet: .75,
+          subsetId: generateSubsetId()
         }, keystrokeDistributions[i]);
       };
 
@@ -406,6 +438,7 @@ describe('ContextToken', function() {
         ]
       ];
       const splitTextArray = ['big', 'large', 'transform'];
+      const subsetId = generateSubsetId();
 
       const tokenToSplit = new ContextToken(plainModel);
       for(let i = 0; i < keystrokeDistributions.length; i++) {
@@ -415,7 +448,8 @@ describe('ContextToken', function() {
             transitionId: keystrokeDistributions[i][0].sample.id,
             start: 0
           },
-          bestProbFromSet: 1
+          bestProbFromSet: 1,
+          subsetId
         }, keystrokeDistributions[i]);
       };
 
@@ -449,7 +483,8 @@ describe('ContextToken', function() {
           transitionId: keystrokeDistributions[0][0].sample.id,
           start: i
         },
-        bestProbFromSet: 1
+        bestProbFromSet: 1,
+        subsetId
       })));
 
       for(let i = 0; i < resultsOfSplit.length; i++) {
@@ -472,6 +507,11 @@ describe('ContextToken', function() {
         ]
       ];
       const splitTextArray = ['large', 'long', 'transforms'];
+      const subsetIds = [
+        generateSubsetId(),
+        generateSubsetId(),
+        generateSubsetId()
+      ];
 
       const tokenToSplit = new ContextToken(plainModel);
       for(let i = 0; i < keystrokeDistributions.length; i++) {
@@ -481,7 +521,8 @@ describe('ContextToken', function() {
             transitionId: keystrokeDistributions[i][0].sample.id,
             start: 0
           },
-          bestProbFromSet: 1
+          bestProbFromSet: 1,
+          subsetId: subsetIds[i]
         }, keystrokeDistributions[i]);
       };
 
@@ -511,14 +552,16 @@ describe('ContextToken', function() {
             transitionId: keystrokeDistributions[0][0].sample.id,
             start: 0
           },
-          bestProbFromSet: 1
+          bestProbFromSet: 1,
+          subsetId: subsetIds[0]
         }, {
           segment: {
             trueTransform: keystrokeDistributions[1][0].sample,
             transitionId: keystrokeDistributions[1][0].sample.id,
             start: 0
           },
-          bestProbFromSet: 1
+          bestProbFromSet: 1,
+          subsetId: subsetIds[1]
         },
       ]);
       assert.deepEqual(resultsOfSplit[1].inputSegments, [
@@ -528,14 +571,16 @@ describe('ContextToken', function() {
             transitionId: keystrokeDistributions[1][0].sample.id,
             start: 'arge'.length
           },
-          bestProbFromSet: 1
+          bestProbFromSet: 1,
+          subsetId: subsetIds[1]
         }, {
           segment: {
             trueTransform: keystrokeDistributions[2][0].sample,
             transitionId: keystrokeDistributions[2][0].sample.id,
             start: 0
           },
-          bestProbFromSet: 1
+          bestProbFromSet: 1,
+          subsetId: subsetIds[2]
         },
       ]);
       assert.deepEqual(resultsOfSplit[2].inputSegments, [
@@ -545,7 +590,8 @@ describe('ContextToken', function() {
             transitionId: keystrokeDistributions[2][0].sample.id,
             start: 'ng'.length,
           },
-          bestProbFromSet: 1
+          bestProbFromSet: 1,
+          subsetId: subsetIds[2]
         }
       ]);
 
@@ -612,6 +658,11 @@ describe('ContextToken', function() {
         ]
       ];
       const splitTextArray = ['large', 'long', 'transforms'].map(t => toMathematicalSMP(t));
+      const subsetIds = [
+        generateSubsetId(),
+        generateSubsetId(),
+        generateSubsetId()
+      ];
 
       const tokenToSplit = new ContextToken(plainModel);
       for(let i = 0; i < keystrokeDistributions.length; i++) {
@@ -621,7 +672,8 @@ describe('ContextToken', function() {
             transitionId: keystrokeDistributions[i][0].sample.id,
             start: 0
           },
-          bestProbFromSet: 1
+          bestProbFromSet: 1,
+          subsetId: subsetIds[i]
         }, keystrokeDistributions[i]);
       };
 
@@ -650,14 +702,16 @@ describe('ContextToken', function() {
             transitionId: keystrokeDistributions[0][0].sample.id,
             start: 0
           },
-          bestProbFromSet: 1
+          bestProbFromSet: 1,
+          subsetId: subsetIds[0]
         }, {
           segment: {
             trueTransform: keystrokeDistributions[1][0].sample,
             transitionId: keystrokeDistributions[1][0].sample.id,
             start: 0
           },
-          bestProbFromSet: 1
+          bestProbFromSet: 1,
+          subsetId: subsetIds[1]
         },
       ]);
       assert.deepEqual(resultsOfSplit[1].inputSegments, [{
@@ -666,14 +720,16 @@ describe('ContextToken', function() {
             transitionId: keystrokeDistributions[1][0].sample.id,
             start: 'arge'.length
           },
-          bestProbFromSet: 1
+          bestProbFromSet: 1,
+          subsetId: subsetIds[1]
         }, {
           segment: {
             trueTransform: keystrokeDistributions[2][0].sample,
             transitionId: keystrokeDistributions[2][0].sample.id,
             start: 0
           },
-          bestProbFromSet: 1
+          bestProbFromSet: 1,
+          subsetId: subsetIds[2]
         }
       ]);
       assert.deepEqual(resultsOfSplit[2].inputSegments, [{
@@ -682,7 +738,8 @@ describe('ContextToken', function() {
           transitionId: keystrokeDistributions[2][0].sample.id,
           start: 'ng'.length
         },
-        bestProbFromSet: 1
+        bestProbFromSet: 1,
+        subsetId: subsetIds[2]
       }]);
 
       assert.isTrue(quotientPathHasInputs(
@@ -746,13 +803,20 @@ describe('preprocessInputSources', () => {
       { insert: 'ngtransforms', deleteLeft: 4, deleteRight: 0, id: 13 }
     ];
 
+    const subsetIds = [
+      generateSubsetId(),
+      generateSubsetId(),
+      generateSubsetId()
+    ];
+
     const results = preprocessInputSources(transforms.map((t, i) => ({
       segment: {
         trueTransform: t,
         transitionId: t.id,
         start: 0
       },
-      bestProbFromSet: 1
+      bestProbFromSet: 1,
+      subsetId: subsetIds[i]
     })));
 
     assert.equal(results.length, transforms.length);
diff --git a/web/src/test/auto/headless/engine/predictive-text/worker-thread/context/context-tokenization.tests.ts b/web/src/test/auto/headless/engine/predictive-text/worker-thread/context/context-tokenization.tests.ts
index 2a5dcd59614..3adf8585c48 100644
--- a/web/src/test/auto/headless/engine/predictive-text/worker-thread/context/context-tokenization.tests.ts
+++ b/web/src/test/auto/headless/engine/predictive-text/worker-thread/context/context-tokenization.tests.ts
@@ -24,6 +24,7 @@ import {
   EditOperation,
   EditTuple,
   ExtendedEditOperation,
+  generateSubsetId,
   models,
   PendingTokenization,
   SearchQuotientSpur,
@@ -54,7 +55,8 @@ function toTransformToken(text: string, transformId?: number) {
       trueTransform: textAsTransform,
       transitionId: textAsTransform.id,
       start: 0
-    }, bestProbFromSet: 1
+    }, bestProbFromSet: 1,
+    subsetId: generateSubsetId()
   }, [ { sample: textAsTransform, p: 1 } ]);
   token.isWhitespace = isWhitespace;
   return token;
@@ -120,7 +122,8 @@ describe('ContextTokenization', function() {
           const map = new Map<number, Transform>();
           map.set(0, emptyTransform);
           return map;
-        })(), p: 1}]
+        })(), p: 1}],
+        inputSubsetId: generateSubsetId()
       };
 
       let tokenization = new ContextTokenization(tokens, transitionEdits, null /* dummy val */);
@@ -152,7 +155,8 @@ describe('ContextTokenization', function() {
           const map = new Map<number, Transform>();
           map.set(0, emptyTransform);
           return map;
-        })(), p: 1}]
+        })(), p: 1}],
+        inputSubsetId: generateSubsetId()
       };
 
       let baseTokenization = new ContextTokenization(tokens, transitionEdits, null /* dummy val */);
@@ -206,7 +210,8 @@ describe('ContextTokenization', function() {
           },
           removedTokenCount: 0
         },
-        inputs: [{ sample: inputTransformMap, p: 1 }]
+        inputs: [{ sample: inputTransformMap, p: 1 }],
+        inputSubsetId: generateSubsetId()
       },
         plainModel,
         inputTransform,
@@ -259,7 +264,8 @@ describe('ContextTokenization', function() {
           },
           removedTokenCount: 2
         },
-        inputs: [{ sample: inputTransformMap, p: 1 }]
+        inputs: [{ sample: inputTransformMap, p: 1 }],
+        inputSubsetId: generateSubsetId()
       },
         plainModel,
         inputTransform,
@@ -296,7 +302,8 @@ describe('ContextTokenization', function() {
           },
           removedTokenCount: 0
         },
-        inputs: [{ sample: inputTransformMap, p: 1 }]
+        inputs: [{ sample: inputTransformMap, p: 1 }],
+        inputSubsetId: generateSubsetId()
       },
         plainModel,
         inputTransform,
@@ -342,7 +349,8 @@ describe('ContextTokenization', function() {
           },
           removedTokenCount: 0
         },
-        inputs: [{ sample: inputTransformMap, p: 1 }]
+        inputs: [{ sample: inputTransformMap, p: 1 }],
+        inputSubsetId: generateSubsetId()
       },
         plainModel,
         inputTransform,
@@ -398,7 +406,8 @@ describe('ContextTokenization', function() {
           },
           removedTokenCount: 0
         },
-        inputs: [{ sample: inputTransformMap, p: 1 }]
+        inputs: [{ sample: inputTransformMap, p: 1 }],
+        inputSubsetId: generateSubsetId()
       },
         plainModel,
         inputTransform,
@@ -437,6 +446,7 @@ describe('ContextTokenization', function() {
       inputTransformMap.set( 0, { insert: 'day', deleteLeft: 6, id: 42 });
 
       const edgeWindow = buildEdgeWindow(baseTokenization.tokens, inputTransform, false, testEdgeWindowSpec);
+      const subsetId = generateSubsetId();
       const tokenization = baseTokenization.evaluateTransition({
         alignment: {
           merges: [],
@@ -449,7 +459,8 @@ describe('ContextTokenization', function() {
           },
           removedTokenCount: 0
         },
-        inputs: [{ sample: inputTransformMap, p: 1 }]
+        inputs: [{ sample: inputTransformMap, p: 1 }],
+        inputSubsetId: subsetId
       },
         plainModel,
         inputTransform,
@@ -469,7 +480,8 @@ describe('ContextTokenization', function() {
           trueTransform: inputTransform,
           transitionId: inputTransform.id,
           start: 0
-        }, bestProbFromSet: 1
+        }, bestProbFromSet: 1,
+        subsetId
       });
 
       // The new tail tokens should not include anything from the original tail;
@@ -479,7 +491,8 @@ describe('ContextTokenization', function() {
           trueTransform: inputTransform,
           transitionId: inputTransform.id,
           start: 0
-        }, bestProbFromSet: 1
+        }, bestProbFromSet: 1,
+        subsetId
       }]);
       assert.deepEqual(tokenization.tokens[tokenization.tokens.length-1].inputSegments, [{
         segment: {
@@ -487,7 +500,8 @@ describe('ContextTokenization', function() {
           transitionId: inputTransform.id,
           start: 1
         },
-        bestProbFromSet: 1
+        bestProbFromSet: 1,
+        subsetId
       }]);
 
       const tailIndex = tokenization.tokens.length - 1;
@@ -530,7 +544,8 @@ describe('ContextTokenization', function() {
           },
           removedTokenCount: 0
         },
-        inputs: [{ sample: inputTransformMap, p: 1 }]
+        inputs: [{ sample: inputTransformMap, p: 1 }],
+        inputSubsetId: generateSubsetId()
       },
         plainModel,
         { insert: ' ', deleteLeft: 0 },
@@ -593,7 +608,8 @@ describe('ContextTokenization', function() {
           },
           removedTokenCount: 0
         },
-        inputs: [{ sample: inputTransformMap, p: 1 }]
+        inputs: [{ sample: inputTransformMap, p: 1 }],
+        inputSubsetId: generateSubsetId()
       },
         plainModel,
         { insert: 't', deleteLeft: 0 },
@@ -659,7 +675,8 @@ describe('ContextTokenization', function() {
           },
           removedTokenCount: 0
         },
-        inputs: [{ sample: inputTransformMap, p: 1 }]
+        inputs: [{ sample: inputTransformMap, p: 1 }],
+        inputSubsetId: generateSubsetId()
       },
         plainModel,
         inputTransform,
diff --git a/web/src/test/auto/headless/engine/predictive-text/worker-thread/context/tokenization-subsets.tests.ts b/web/src/test/auto/headless/engine/predictive-text/worker-thread/context/tokenization-subsets.tests.ts
index 880ad7782f3..073c780744e 100644
--- a/web/src/test/auto/headless/engine/predictive-text/worker-thread/context/tokenization-subsets.tests.ts
+++ b/web/src/test/auto/headless/engine/predictive-text/worker-thread/context/tokenization-subsets.tests.ts
@@ -20,6 +20,7 @@ import {
   buildEdgeWindow,
   ContextToken,
   ContextTokenization,
+  generateSubsetId,
   models,
   precomputationSubsetKeyer,
   TokenizationTransitionEdits,
@@ -188,7 +189,8 @@ describe('precomputationSubsetKeyer', function() {
                   id: 13
                 }, transitionId: 13,
                 start: 0
-              }, bestProbFromSet: 1
+              }, bestProbFromSet: 1,
+              subsetId: generateSubsetId()
             }, [
               {sample: {insert: 'te', deleteLeft: 0, id: 13}, p: 1}
             ]);
@@ -223,7 +225,8 @@ describe('precomputationSubsetKeyer', function() {
                   id: 13
                 }, transitionId: 13,
                 start: 0
-              }, bestProbFromSet: 1
+              }, bestProbFromSet: 1,
+              subsetId: generateSubsetId()
             }, [
               {sample: {insert: 't', deleteLeft: 0}, p: 1}
             ]);
@@ -272,7 +275,8 @@ describe('precomputationSubsetKeyer', function() {
                     id: 13
                   }, transitionId: 13,
                   start: 0
-                }, bestProbFromSet: 1
+                }, bestProbFromSet: 1,
+                subsetId: generateSubsetId()
               }, [{sample: {insert: 'ts', deleteLeft: 0, id: 13}, p: 1}
               ]);
               return token;
@@ -307,7 +311,8 @@ describe('precomputationSubsetKeyer', function() {
                 id: 13
               }, transitionId: 13,
               start: 0
-            }, bestProbFromSet: 1
+            }, bestProbFromSet: 1,
+            subsetId: generateSubsetId()
           }, [
             {sample: {insert: 't', deleteLeft: 0, id: 13}, p: 1}
           ]);
@@ -767,7 +772,8 @@ describe('TokenizationSubsetBuilder', function() {
           id: 13
         }, transitionId: 13,
         start: 0
-      }, bestProbFromSet: 1
+      }, bestProbFromSet: 1,
+      subsetId: generateSubsetId()
     }, [
       { sample: trueSourceTransform, p: .6 }
     ]);
@@ -781,7 +787,8 @@ describe('TokenizationSubsetBuilder', function() {
           id: 13
         }, transitionId: 13,
         start: 0
-      }, bestProbFromSet: 1
+      }, bestProbFromSet: 1,
+      subsetId: generateSubsetId()
     }, [
       { sample: { insert: 's', deleteLeft: 0, id: 13 }, p: .4 }
     ]);
@@ -822,7 +829,8 @@ describe('TokenizationSubsetBuilder', function() {
           id: 13
         }, transitionId: 13,
         start: 0
-      }, bestProbFromSet: .6
+      }, bestProbFromSet: .6,
+      subsetId: generateSubsetId()
     }, [
       { sample: trueSourceTransform, p: .6 }
     ]);
@@ -835,7 +843,8 @@ describe('TokenizationSubsetBuilder', function() {
           deleteLeft: 1
         }, transitionId: 13,
         start: 0
-      }, bestProbFromSet: .6
+      }, bestProbFromSet: .6,
+      subsetId: generateSubsetId()
     }, [
       { sample: { insert: 'a', deleteLeft: 0, id: 13}, p: .4 }
     ]);
diff --git a/web/src/test/auto/headless/engine/predictive-text/worker-thread/correction-search/search-quotient-spur.tests.ts b/web/src/test/auto/headless/engine/predictive-text/worker-thread/correction-search/search-quotient-spur.tests.ts
index 5554e05e1ed..837d5e0cae3 100644
--- a/web/src/test/auto/headless/engine/predictive-text/worker-thread/correction-search/search-quotient-spur.tests.ts
+++ b/web/src/test/auto/headless/engine/predictive-text/worker-thread/correction-search/search-quotient-spur.tests.ts
@@ -83,7 +83,9 @@ describe('SearchQuotientSpur', () => {
             transitionId: leadEdgeDistribution[0].sample.id,
             start: 0
           },
-          bestProbFromSet: leadEdgeDistribution[0].p
+          bestProbFromSet: leadEdgeDistribution[0].p,
+          // Just write in the variable-value entry; the rest should match perfectly.
+          subsetId: extendedPath.inputSegments[0].subsetId
         }
       ]);
 
@@ -138,14 +140,18 @@ describe('SearchQuotientSpur', () => {
             transitionId: leadEdgeDistribution[0].sample.id,
             start: 0
           },
-          bestProbFromSet: leadEdgeDistribution[0].p
+          bestProbFromSet: leadEdgeDistribution[0].p,
+          // Just write in the variable-value entry; the rest should match perfectly.
+          subsetId: length2Path.inputSegments[0].subsetId
         }, {
           segment: {
             trueTransform: tailEdgeDistribution[0].sample,
             transitionId: tailEdgeDistribution[0].sample.id,
             start: 0
           },
-          bestProbFromSet: tailEdgeDistribution[0].p
+          bestProbFromSet: tailEdgeDistribution[0].p,
+          // Just write in the variable-value entry; the rest should match perfectly.
+          subsetId: length2Path.inputSegments[1].subsetId
         }
       ]);
 
@@ -216,14 +222,18 @@ describe('SearchQuotientSpur', () => {
             transitionId: leadEdgeDistribution[0].sample.id,
             start: 0
           },
-          bestProbFromSet: leadEdgeDistribution[0].p
+          bestProbFromSet: leadEdgeDistribution[0].p,
+          // Just write in the variable-value entry; the rest should match perfectly.
+          subsetId: length2Path.inputSegments[0].subsetId
         }, {
           segment: {
             trueTransform: tailEdgeDistribution[0].sample,
             transitionId: tailEdgeDistribution[0].sample.id,
             start: 0
           },
-          bestProbFromSet: tailEdgeDistribution[0].p
+          bestProbFromSet: tailEdgeDistribution[0].p,
+          // Just write in the variable-value entry; the rest should match perfectly.
+          subsetId: length2Path.inputSegments[1].subsetId
         }
       ]);