diff --git a/deploy/nl/catalog.yaml b/deploy/nl/catalog.yaml
index af3a474e90..bc4c3a638d 100644
--- a/deploy/nl/catalog.yaml
+++ b/deploy/nl/catalog.yaml
@@ -90,7 +90,7 @@ indexes:
   base_uae_mem:
     store_type: MEMORY
     source_path: ../../tools/nl/embeddings/input/base
-    embeddings_path: gs://datcom-nl-models/base_uae_mem_2024_07_11_08_35_57/embeddings.csv
+    embeddings_path: gs://datcom-nl-models/base_uae_mem_2024_07_12_09_03_25/embeddings.csv
     model: uae-large-v1-model
     healthcheck_query: "Life expectancy"
   base_mistral_mem:
diff --git a/run_test.sh b/run_test.sh
index bb6c4aa754..6d37dc3b8b 100755
--- a/run_test.sh
+++ b/run_test.sh
@@ -64,7 +64,7 @@ function run_lint_fix {
     pip3 install isort -q
   fi
   yapf -r -i -p --style='{based_on_style: google, indent_width: 2}' server/ nl_server/ shared/ tools/ -e=*pb2.py -e=**/.env/**
-  isort server/ nl_server/ shared/ tools/  --skip-glob *pb2.py  --skip-glob **/.env/** --profile google
+  isort server/ nl_server/ shared/ tools/  --skip-glob=*pb2.py  --skip-glob=**/.env/** --profile=google
   deactivate
 }
 
diff --git a/server/integration_tests/test_data/demo_fallback/query_2/chart_config.json b/server/integration_tests/test_data/demo_fallback/query_2/chart_config.json
index 4debf0ea5a..e604f84cda 100644
--- a/server/integration_tests/test_data/demo_fallback/query_2/chart_config.json
+++ b/server/integration_tests/test_data/demo_fallback/query_2/chart_config.json
@@ -78,16 +78,16 @@
                       "geoId/12"
                     ],
                     "statVarKey": [
-                      "Count_CriminalIncidents_IsHateCrime_multiple_place_bar_block"
+                      "Count_CriminalActivities_MurderAndNonNegligentManslaughter_multiple_place_bar_block"
                     ],
-                    "title": "Hate Crime Incidents (${date})",
+                    "title": "Murder and Non Negligent Manslaughter Cases (${date})",
                     "type": "BAR"
                   }
                 ]
               }
             ],
             "denom": "Count_Person",
-            "title": "Hate Crime Incidents"
+            "title": "Murder and Non Negligent Manslaughter Cases"
           },
           {
             "columns": [
@@ -104,17 +104,16 @@
                       "geoId/12"
                     ],
                     "statVarKey": [
-                      "Count_CriminalIncidents_BiasMotivationDisabilityStatus_AggravatedAssault_IsHateCrime_multiple_place_bar_block",
-                      "Count_CriminalIncidents_BiasMotivationDisabilityStatus_Robbery_IsHateCrime_multiple_place_bar_block"
+                      "Count_CriminalIncidents_IsHateCrime_multiple_place_bar_block"
                     ],
-                    "title": "Hate Crime Cases by Type (${date})",
+                    "title": "Hate Crime Incidents (${date})",
                     "type": "BAR"
                   }
                 ]
               }
             ],
             "denom": "Count_Person",
-            "title": "Hate Crime Cases by Type"
+            "title": "Hate Crime Incidents"
           },
           {
             "columns": [
@@ -131,16 +130,17 @@
                       "geoId/12"
                     ],
                     "statVarKey": [
-                      "Count_CriminalActivities_MurderAndNonNegligentManslaughter_multiple_place_bar_block"
+                      "Count_CriminalIncidents_BiasMotivationDisabilityStatus_AggravatedAssault_IsHateCrime_multiple_place_bar_block",
+                      "Count_CriminalIncidents_BiasMotivationDisabilityStatus_Robbery_IsHateCrime_multiple_place_bar_block"
                     ],
-                    "title": "Murder and Non Negligent Manslaughter Cases (${date})",
+                    "title": "Hate Crime Cases by Type (${date})",
                     "type": "BAR"
                   }
                 ]
               }
             ],
             "denom": "Count_Person",
-            "title": "Murder and Non Negligent Manslaughter Cases"
+            "title": "Hate Crime Cases by Type"
           },
           {
             "columns": [
diff --git a/server/integration_tests/test_data/demo_fallback/query_3/chart_config.json b/server/integration_tests/test_data/demo_fallback/query_3/chart_config.json
index 80fa38be66..5480ad727c 100644
--- a/server/integration_tests/test_data/demo_fallback/query_3/chart_config.json
+++ b/server/integration_tests/test_data/demo_fallback/query_3/chart_config.json
@@ -71,9 +71,9 @@
                 "tiles": [
                   {
                     "statVarKey": [
-                      "Count_CriminalIncidents_IsHateCrime"
+                      "Count_CriminalActivities_MurderAndNonNegligentManslaughter"
                     ],
-                    "title": "Hate Crime Incidents in California",
+                    "title": "Murder and Non Negligent Manslaughter Cases in California",
                     "type": "LINE"
                   }
                 ]
@@ -81,18 +81,18 @@
               {
                 "tiles": [
                   {
-                    "description": "Hate Crime Incidents in California",
+                    "description": "Murder and Non Negligent Manslaughter Cases in California",
                     "statVarKey": [
-                      "Count_CriminalIncidents_IsHateCrime"
+                      "Count_CriminalActivities_MurderAndNonNegligentManslaughter"
                     ],
-                    "title": "Hate Crime Incidents in California",
+                    "title": "Murder and Non Negligent Manslaughter Cases in California",
                     "type": "HIGHLIGHT"
                   }
                 ]
               }
             ],
             "denom": "Count_Person",
-            "title": "Hate Crime Incidents"
+            "title": "Murder and Non Negligent Manslaughter Cases"
           },
           {
             "columns": [
@@ -100,47 +100,47 @@
                 "tiles": [
                   {
                     "statVarKey": [
-                      "Count_CriminalIncidents_BiasMotivationDisabilityStatus_AggravatedAssault_IsHateCrime",
-                      "Count_CriminalIncidents_BiasMotivationDisabilityStatus_Intimidation_IsHateCrime",
-                      "Count_CriminalIncidents_BiasMotivationDisabilityStatus_Robbery_IsHateCrime"
+                      "Count_CriminalIncidents_IsHateCrime"
                     ],
-                    "title": "Hate Crime Cases by Type in California",
+                    "title": "Hate Crime Incidents in California",
                     "type": "LINE"
                   }
                 ]
-              }
-            ],
-            "denom": "Count_Person",
-            "title": "Hate Crime Cases by Type"
-          },
-          {
-            "columns": [
+              },
               {
                 "tiles": [
                   {
+                    "description": "Hate Crime Incidents in California",
                     "statVarKey": [
-                      "Count_CriminalActivities_MurderAndNonNegligentManslaughter"
+                      "Count_CriminalIncidents_IsHateCrime"
                     ],
-                    "title": "Murder and Non Negligent Manslaughter Cases in California",
-                    "type": "LINE"
+                    "title": "Hate Crime Incidents in California",
+                    "type": "HIGHLIGHT"
                   }
                 ]
-              },
+              }
+            ],
+            "denom": "Count_Person",
+            "title": "Hate Crime Incidents"
+          },
+          {
+            "columns": [
               {
                 "tiles": [
                   {
-                    "description": "Murder and Non Negligent Manslaughter Cases in California",
                     "statVarKey": [
-                      "Count_CriminalActivities_MurderAndNonNegligentManslaughter"
+                      "Count_CriminalIncidents_BiasMotivationDisabilityStatus_AggravatedAssault_IsHateCrime",
+                      "Count_CriminalIncidents_BiasMotivationDisabilityStatus_Intimidation_IsHateCrime",
+                      "Count_CriminalIncidents_BiasMotivationDisabilityStatus_Robbery_IsHateCrime"
                     ],
-                    "title": "Murder and Non Negligent Manslaughter Cases in California",
-                    "type": "HIGHLIGHT"
+                    "title": "Hate Crime Cases by Type in California",
+                    "type": "LINE"
                   }
                 ]
               }
             ],
             "denom": "Count_Person",
-            "title": "Murder and Non Negligent Manslaughter Cases"
+            "title": "Hate Crime Cases by Type"
           },
           {
             "columns": [
diff --git a/server/integration_tests/test_data/detection_api_multivar/comparemalepopulationwithfemalepopulation/debug_info.json b/server/integration_tests/test_data/detection_api_multivar/comparemalepopulationwithfemalepopulation/debug_info.json
index c6f926b5fc..4e8170d3c4 100644
--- a/server/integration_tests/test_data/detection_api_multivar/comparemalepopulationwithfemalepopulation/debug_info.json
+++ b/server/integration_tests/test_data/detection_api_multivar/comparemalepopulationwithfemalepopulation/debug_info.json
@@ -54,7 +54,7 @@
           "Parts": [
             {
               "CosineScore": [
-                0.9257857799530029
+                0.9257858991622925
               ],
               "QueryPart": "male population",
               "SV": [
@@ -63,8 +63,8 @@
             },
             {
               "CosineScore": [
-                0.9296980500221252,
-                0.8847433924674988
+                0.9296978712081909,
+                0.884743332862854
               ],
               "QueryPart": "female population",
               "SV": [
@@ -80,7 +80,7 @@
           "Parts": [
             {
               "CosineScore": [
-                0.9117770791053772
+                0.911777138710022
               ],
               "QueryPart": "male population female",
               "SV": [
@@ -89,8 +89,8 @@
             },
             {
               "CosineScore": [
-                0.8982378840446472,
-                0.8723467588424683
+                0.8982377648353577,
+                0.8723466396331787
               ],
               "QueryPart": "population",
               "SV": [
@@ -106,9 +106,9 @@
           "Parts": [
             {
               "CosineScore": [
-                0.8034241199493408,
-                0.8017654418945312,
-                0.775155782699585,
+                0.8034241795539856,
+                0.8017653822898865,
+                0.7751558423042297,
                 0.7698014974594116,
                 0.7586972713470459
               ],
diff --git a/server/integration_tests/test_data/detection_api_multivar/howarefactorslikeobesity,bloodpressureandasthmaimpactedbyclimatechange/debug_info.json b/server/integration_tests/test_data/detection_api_multivar/howarefactorslikeobesity,bloodpressureandasthmaimpactedbyclimatechange/debug_info.json
index 0c125dcdfd..4f89c0a024 100644
--- a/server/integration_tests/test_data/detection_api_multivar/howarefactorslikeobesity,bloodpressureandasthmaimpactedbyclimatechange/debug_info.json
+++ b/server/integration_tests/test_data/detection_api_multivar/howarefactorslikeobesity,bloodpressureandasthmaimpactedbyclimatechange/debug_info.json
@@ -113,10 +113,10 @@
           "Parts": [
             {
               "CosineScore": [
-                0.7768431901931763,
-                0.7495046257972717,
-                0.7342654466629028,
-                0.7325114011764526
+                0.7768430709838867,
+                0.749504566192627,
+                0.7342653274536133,
+                0.7325113415718079
               ],
               "QueryPart": "factors like obesity blood pressure asthma",
               "SV": [
@@ -128,7 +128,7 @@
             },
             {
               "CosineScore": [
-                0.9056920409202576
+                0.9056921005249023
               ],
               "QueryPart": "impacted climate change",
               "SV": [
diff --git a/server/integration_tests/test_data/detection_translate_chinese/chart_config.json b/server/integration_tests/test_data/detection_translate_chinese/chart_config.json
index 9e7293495c..b2885090eb 100644
--- a/server/integration_tests/test_data/detection_translate_chinese/chart_config.json
+++ b/server/integration_tests/test_data/detection_translate_chinese/chart_config.json
@@ -11,9 +11,6 @@
       "contained_in_place_type": "City",
       "had_default_type": false,
       "type": 4
-    },
-    {
-      "type": 14
     }
   ],
   "client": "test_detect",
diff --git a/server/integration_tests/test_data/e2e_edge_cases2/povertyvs.unemploymentrateindistrictsoftamilnadu/chart_config.json b/server/integration_tests/test_data/e2e_edge_cases2/povertyvs.unemploymentrateindistrictsoftamilnadu/chart_config.json
index b053c625e5..9af6fd1c7c 100644
--- a/server/integration_tests/test_data/e2e_edge_cases2/povertyvs.unemploymentrateindistrictsoftamilnadu/chart_config.json
+++ b/server/integration_tests/test_data/e2e_edge_cases2/povertyvs.unemploymentrateindistrictsoftamilnadu/chart_config.json
@@ -31,7 +31,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Population Below Poverty Line"
           },
           {
diff --git a/server/integration_tests/test_data/e2e_high_sv_threshold/chart_config.json b/server/integration_tests/test_data/e2e_high_sv_threshold/chart_config.json
index a78e115aac..fc7fd99909 100644
--- a/server/integration_tests/test_data/e2e_high_sv_threshold/chart_config.json
+++ b/server/integration_tests/test_data/e2e_high_sv_threshold/chart_config.json
@@ -62,7 +62,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Count of Mortality Event: 1 Years or Less in Counties of Massachusetts"
           },
           {
@@ -83,7 +82,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Causes of Infant Mortality"
           },
           {
@@ -116,7 +114,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Mortality Events (1 Years or Less): Symptoms, Signs and Abnormal Clinical and Laboratory Findings, Not Elsewhere Classified) in Counties of Massachusetts"
           },
           {
@@ -149,7 +146,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Mortality Events (1 Years or Less): Certain Conditions Originating in the Perinatal Period) in Counties of Massachusetts"
           },
           {
diff --git a/server/integration_tests/test_data/e2e_india_demo/howdoesliteracyratecomparetopovertyinindia/chart_config.json b/server/integration_tests/test_data/e2e_india_demo/howdoesliteracyratecomparetopovertyinindia/chart_config.json
index be3e6d0b80..9425dcb40d 100644
--- a/server/integration_tests/test_data/e2e_india_demo/howdoesliteracyratecomparetopovertyinindia/chart_config.json
+++ b/server/integration_tests/test_data/e2e_india_demo/howdoesliteracyratecomparetopovertyinindia/chart_config.json
@@ -23,7 +23,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Population: Literate vs. Population Below poverty line"
           },
           {
@@ -56,7 +55,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Population: Literate in Administrative Area 1 Places of India"
           },
           {
@@ -89,7 +87,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Population Below Poverty Line in Administrative Area 1 Places of India"
           },
           {
@@ -111,7 +108,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Population: Illiterate vs. Population Below poverty line (Per Capita)"
           },
           {
@@ -195,7 +191,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Population: Literate vs. Population Below poverty line (Per Capita)"
           },
           {
@@ -217,7 +212,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Population: Illiterate vs. Population Below poverty line"
           }
         ],
diff --git a/server/integration_tests/test_data/e2e_india_demo/howdoestheliteracyratecompare/chart_config.json b/server/integration_tests/test_data/e2e_india_demo/howdoestheliteracyratecompare/chart_config.json
index bbe01500ef..c0e50c2620 100644
--- a/server/integration_tests/test_data/e2e_india_demo/howdoestheliteracyratecompare/chart_config.json
+++ b/server/integration_tests/test_data/e2e_india_demo/howdoestheliteracyratecompare/chart_config.json
@@ -36,7 +36,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Population: Literate"
           },
           {
@@ -71,7 +70,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Population: Illiterate"
           },
           {
@@ -139,7 +137,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Population: Literate, Urban"
           },
           {
@@ -174,7 +171,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Population: Male, Literate"
           },
           {
@@ -209,7 +205,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Population: Literate, Rural"
           },
           {
@@ -244,7 +239,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Population: Illiterate, Urban"
           },
           {
@@ -279,7 +273,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Population: Female, Literate"
           },
           {
@@ -314,7 +307,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Population: Male, Illiterate"
           },
           {
@@ -349,7 +341,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Population: Illiterate, Rural"
           },
           {
@@ -384,7 +375,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Population: Female, Illiterate"
           },
           {
@@ -419,7 +409,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Population: Houseless, Literate"
           },
           {
@@ -454,7 +443,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Population: Houseless, Illiterate"
           },
           {
@@ -489,7 +477,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Population: Houseless, Literate, Urban"
           },
           {
@@ -524,7 +511,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Population: Houseless, Illiterate, Urban"
           },
           {
@@ -559,7 +545,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Population: Houseless, Literate, Rural"
           }
         ],
diff --git a/server/integration_tests/test_data/e2e_toolformer_rig_mode/whatistheinfantmortalityrateinmassachusetts/chart_config.json b/server/integration_tests/test_data/e2e_toolformer_rig_mode/whatistheinfantmortalityrateinmassachusetts/chart_config.json
index d15f3e6c0a..5ef8a767ca 100644
--- a/server/integration_tests/test_data/e2e_toolformer_rig_mode/whatistheinfantmortalityrateinmassachusetts/chart_config.json
+++ b/server/integration_tests/test_data/e2e_toolformer_rig_mode/whatistheinfantmortalityrateinmassachusetts/chart_config.json
@@ -115,7 +115,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Mortality Events (1 Years or Less): Certain Conditions Originating in the Perinatal Period)"
           },
           {
@@ -148,7 +147,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Mortality Events (1 Years or Less): Certain Conditions Originating in the Perinatal Period) in Counties of Massachusetts"
           },
           {
@@ -206,7 +204,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Mortality Events (1 Years or Less): Diseases of the Circulatory System"
           },
           {
@@ -236,7 +233,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Mortality Events (1 Years or Less): Q00-Q99 ( Congenital Malformations, Deformations and Chromosomal Abnormalities)"
           },
           {
@@ -269,7 +265,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Mortality Events (1 Years or Less): Q00-Q99 ( Congenital Malformations, Deformations and Chromosomal Abnormalities) in Counties of Massachusetts"
           }
         ],
diff --git a/server/integration_tests/test_data/e2e_toolformer_rig_mode/whatisthepovertyrateinseattle/chart_config.json b/server/integration_tests/test_data/e2e_toolformer_rig_mode/whatisthepovertyrateinseattle/chart_config.json
index e37e40b845..84f31e7a88 100644
--- a/server/integration_tests/test_data/e2e_toolformer_rig_mode/whatisthepovertyrateinseattle/chart_config.json
+++ b/server/integration_tests/test_data/e2e_toolformer_rig_mode/whatisthepovertyrateinseattle/chart_config.json
@@ -31,7 +31,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Population Below Poverty Line"
           },
           {
@@ -61,7 +60,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Below Poverty Line (Two or More Races)"
           },
           {
@@ -91,7 +89,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Males in Poverty (In Last Year)"
           },
           {
@@ -121,7 +118,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Women Below Poverty Line"
           }
         ],
diff --git a/server/integration_tests/test_data/e2e_us_demo/howdoobesityratescomparewithratesofdiabetesinusacounties/chart_config.json b/server/integration_tests/test_data/e2e_us_demo/howdoobesityratescomparewithratesofdiabetesinusacounties/chart_config.json
index 459d5a0bc9..bedf01a74e 100644
--- a/server/integration_tests/test_data/e2e_us_demo/howdoobesityratescomparewithratesofdiabetesinusacounties/chart_config.json
+++ b/server/integration_tests/test_data/e2e_us_demo/howdoobesityratescomparewithratesofdiabetesinusacounties/chart_config.json
@@ -173,7 +173,6 @@
               }
             ],
             "denom": "Count_Person",
-            "startWithDenom": true,
             "title": "Prevalence: Male, Obesity vs. Diabetes"
           },
           {
diff --git a/server/lib/nl/detection/query_util.py b/server/lib/nl/detection/query_util.py
index 0d3972ff12..29067c404b 100644
--- a/server/lib/nl/detection/query_util.py
+++ b/server/lib/nl/detection/query_util.py
@@ -20,12 +20,6 @@
 
 from shared.lib import utils
 
-# TODO: decouple words removal from detected attributes. Today, the removal
-# blanket removes anything that matches, including the various attribute/
-# classification triggers and contained_in place types (and their plurals).
-# This may not always be the best thing to do.
-ALL_STOP_WORDS = utils.combine_stop_words()
-
 # Use comma, "vs.", semi-colon, "and", ampersand as delimiters.
 _REGEX_DELIMITERS = r',|vs|;|and|&'
 # Regex to extract out substrings within double quotes.
@@ -100,14 +94,14 @@ def get_parts_via_delimiters(query):
   return parts
 
 
-def _prepare_queryset_via_delimiters(query: str,
-                                     querysets: List[QuerySet]) -> int:
+def _prepare_queryset_via_delimiters(query: str, querysets: List[QuerySet],
+                                     stop_words: List[str]) -> int:
   parts = get_parts_via_delimiters(query)
   if len(parts) == 1:
     return 0
   cleaned_parts = []
   for p in parts:
-    p = utils.remove_stop_words(utils.remove_punctuations(p), ALL_STOP_WORDS)
+    p = utils.remove_stop_words(utils.remove_punctuations(p), stop_words)
     if p:
       cleaned_parts.append(p)
   if not cleaned_parts:
@@ -123,13 +117,14 @@ def _prepare_queryset_via_delimiters(query: str,
 #
 # Returns combinations of |query| string parts of upto _MAX_SVS splits.
 #
-def prepare_multivar_querysets(query: str, max_svs: int) -> List[QuerySet]:
+def prepare_multivar_querysets(query: str, max_svs: int,
+                               stop_words: List[str]) -> List[QuerySet]:
   querysets: List[QuerySet] = []
 
-  delim_nsplits = _prepare_queryset_via_delimiters(query, querysets)
+  delim_nsplits = _prepare_queryset_via_delimiters(query, querysets, stop_words)
 
   query = utils.remove_punctuations(query)
-  query = utils.remove_stop_words(query, ALL_STOP_WORDS)
+  query = utils.remove_stop_words(query, stop_words)
 
   query_parts = [x.strip() for x in query.split(' ') if x.strip()]
   max_splits = min(max_svs, len(query_parts))
diff --git a/server/lib/nl/detection/variable.py b/server/lib/nl/detection/variable.py
index 81e19f6e8a..800add777d 100644
--- a/server/lib/nl/detection/variable.py
+++ b/server/lib/nl/detection/variable.py
@@ -17,7 +17,6 @@
 
 from typing import Dict, List
 
-import server.lib.nl.common.counters as ctr
 from server.lib.nl.detection import query_util
 from server.lib.nl.detection.types import DetectionArgs
 import server.lib.nl.detection.utils as dutils
@@ -27,12 +26,6 @@
 import shared.lib.detected_variables as vars
 import shared.lib.utils as shared_utils
 
-# TODO: decouple words removal from detected attributes. Today, the removal
-# blanket removes anything that matches, including the various attribute/
-# classification triggers and contained_in place types (and their plurals).
-# This may not always be the best thing to do.
-ALL_STOP_WORDS = shared_utils.combine_stop_words()
-
 # A value higher than the highest score.
 _HIGHEST_SCORE = 1.0
 _INIT_SCORE = (_HIGHEST_SCORE + 0.1)
@@ -49,6 +42,15 @@
 #
 def detect_vars(orig_query: str, debug_logs: Dict,
                 dargs: DetectionArgs) -> vars.VarDetectionResult:
+
+  # Get the list of stop words to use depending on if this is toolformer mode
+  # or not.
+  if params.is_toolformer_mode(dargs.mode):
+    stop_words = shared_utils.combine_stop_words(
+        constants.HEURISTIC_TYPES_IN_VARIABLES_TOOLFORMER)
+  else:
+    stop_words = shared_utils.combine_stop_words()
+
   #
   # 1. Prepare all the queries for embeddings lookup, both mono-var and multi-var.
   #
@@ -60,8 +62,7 @@ def detect_vars(orig_query: str, debug_logs: Dict,
   if dargs.include_stop_words:
     query_monovar = orig_query
   else:
-    query_monovar = shared_utils.remove_stop_words(orig_query,
-                                                   query_util.ALL_STOP_WORDS)
+    query_monovar = shared_utils.remove_stop_words(orig_query, stop_words)
   if not query_monovar.strip():
     # Empty user query!  Return empty results
     return dutils.empty_var_detection_result()
@@ -70,7 +71,8 @@ def detect_vars(orig_query: str, debug_logs: Dict,
   # Try to detect multiple SVs.  Use the original query so that
   # the logic can rely on stop-words like `vs`, `and`, etc as hints
   # for SV delimiters.
-  multi_querysets, multi_queries = _prepare_multivar_queries(orig_query)
+  multi_querysets, multi_queries = _prepare_multivar_queries(
+      orig_query, stop_words)
   all_queries.extend(multi_queries)
 
   #
@@ -108,12 +110,14 @@ def detect_vars(orig_query: str, debug_logs: Dict,
 # TODO: Fix the query upstream to ensure the punctuations aren't stripped.
 #
 def _prepare_multivar_queries(
-    query: str) -> tuple[List[query_util.QuerySet], List[str]]:
+    query: str,
+    stop_words: List[str]) -> tuple[List[query_util.QuerySet], List[str]]:
   #
   # Prepare a combination of query-sets.
   #
   querysets = query_util.prepare_multivar_querysets(query,
-                                                    max_svs=_MAX_MULTIVAR_PARTS)
+                                                    max_svs=_MAX_MULTIVAR_PARTS,
+                                                    stop_words=stop_words)
 
   # Make a unique list of query strings
   all_queries = set()
diff --git a/server/tests/lib/nl/detection/query_util_test.py b/server/tests/lib/nl/detection/query_util_test.py
index 3e95c69907..bef03b2772 100644
--- a/server/tests/lib/nl/detection/query_util_test.py
+++ b/server/tests/lib/nl/detection/query_util_test.py
@@ -21,6 +21,7 @@
 from server.lib.nl.detection.query_util import prepare_multivar_querysets
 from server.lib.nl.detection.query_util import QuerySet
 from server.lib.nl.detection.query_util import QuerySplit
+from shared.lib.utils import combine_stop_words
 
 
 class TestGetPartsViaDelimiters(unittest.TestCase):
@@ -181,4 +182,7 @@ class TestPrepareMultivarQuerysets(unittest.TestCase):
        ]])
   def test_prepare_multivar_querysets(self, query, expected):
     self.maxDiff = None
-    self.assertEqual(prepare_multivar_querysets(query, max_svs=4), expected)
+    self.assertEqual(
+        prepare_multivar_querysets(query,
+                                   max_svs=4,
+                                   stop_words=combine_stop_words()), expected)
diff --git a/shared/lib/constants.py b/shared/lib/constants.py
index 81711eef1c..0efb69859e 100644
--- a/shared/lib/constants.py
+++ b/shared/lib/constants.py
@@ -15,6 +15,8 @@
 
 from typing import Dict, FrozenSet, List, Set, Union
 
+_RATE_WORDS_TO_SKIP = "(birth|change|death|exchange|fertility|literacy|mortality|participation|unemployment|withdrawal)"
+
 STOP_WORDS: Set[str] = {
     'ourselves',
     'hers',
@@ -272,8 +274,14 @@
         # together with ContainedInPlace.
         "AnswerPlacesReference": ["these", "those"],
         "PerCapita": [
-            "fraction", "percent", "percentage", "per capita", "percapita",
-            "per person", "rate", "rates"
+            "fraction",
+            "percent",
+            "percentage",
+            "per capita",
+            "percapita",
+            "per person",
+            # remove "rate" or "rates" if is not followed by certain words (used as one metric)
+            f"\brate(s)?\b(?!\s*{_RATE_WORDS_TO_SKIP}\s+rate(s)?)",
         ],
         "Temporal": [
             # Day of week
@@ -309,10 +317,17 @@
         ]
     }
 
-# We do not want to strip words from events / superlatives / temporal
-# since we want those to match SVs too!
+# By default, we do not want to strip words from these heuristics because they
+# can match SVs too: events / superlatives / temporal / percapita.
+# We want to keep per capita because queries like "theft rates" without the
+# per capita stop words will become "theft" which has trouble matching plurals
+# and stat based descriptions.
 HEURISTIC_TYPES_IN_VARIABLES = frozenset(
     ["Event", "Superlative", "Temporal", "PerCapita"])
+# For toolformer, we do want to strip words from PerCapita heuristics because
+# we care about top matches being more accurate.
+HEURISTIC_TYPES_IN_VARIABLES_TOOLFORMER = frozenset(
+    ["Event", "Superlative", "Temporal"])
 
 PLACE_TYPE_TO_PLURALS: Dict[str, str] = {
     "place": "places",
diff --git a/shared/lib/utils.py b/shared/lib/utils.py
index a01b1d84f9..7b706857f0 100644
--- a/shared/lib/utils.py
+++ b/shared/lib/utils.py
@@ -38,14 +38,15 @@ def _add_to_set_from_list(set_strings: Set[str],
     set_strings.add(v_str.lower())
 
 
-def _add_classification_heuristics(set_strings: Set[str]) -> None:
+def _add_classification_heuristics(set_strings: Set[str],
+                                   heuristics_to_skip: Set[str]) -> None:
   """Adds (in place) relevant stop words in QUERY_CLASSIFICATION_HEURISTICS.
 
     Args:
         set_strings: the set of Strings to add to.
     """
   for (ctype, v) in constants.QUERY_CLASSIFICATION_HEURISTICS.items():
-    if ctype in constants.HEURISTIC_TYPES_IN_VARIABLES:
+    if ctype in heuristics_to_skip:
       continue
     if isinstance(v, list):
       # If 'v' is a list, add all the words.
@@ -131,13 +132,19 @@ def list_place_type_stopwords() -> List[str]:
   return place_type_stop_words
 
 
-def combine_stop_words() -> Set[str]:
+# TODO: decouple words removal from detected attributes. Today, the removal
+# blanket removes anything that matches, including the various attribute/
+# classification triggers and contained_in place types (and their plurals).
+# This may not always be the best thing to do.
+def combine_stop_words(
+    heuristics_to_skip: Set[str] = constants.HEURISTIC_TYPES_IN_VARIABLES
+) -> List[str]:
   """Returns all the combined stop words from the various constants."""
   # Make a copy.
   stop_words = copy.deepcopy(constants.STOP_WORDS)
 
   # Now add the words in the classification heuristics.
-  _add_classification_heuristics(stop_words)
+  _add_classification_heuristics(stop_words, heuristics_to_skip)
 
   _add_to_set_from_list(stop_words, list_place_type_stopwords())
 
diff --git a/tools/nl/embeddings/input/base/_preindex.csv b/tools/nl/embeddings/input/base/_preindex.csv
index 29252d54bb..303ef92200 100644
--- a/tools/nl/embeddings/input/base/_preindex.csv
+++ b/tools/nl/embeddings/input/base/_preindex.csv
@@ -1802,7 +1802,7 @@ Number of Merchant Wholesalers establishments,Count_Establishment_USC_MerchantWh
 Number of Milk Cows in Farm Inventory,Count_FarmInventory_MilkCows
 "Number of Mining, Quarrying, And Oil And Gas Extraction establishments",Count_Establishment_NAICSMiningQuarryingOilGasExtraction;dc/br6elkd593zs1
 Number of Mumps Cases,Count_MedicalConditionIncident_ConditionMumps
-Number of Murder and Non Negligent Manslaughter per capita,Count_CriminalActivities_MurderAndNonNegligentManslaughter_AsFractionOf_Count_Person
+Number of Murder and non-negligent manslaughter per capita,Count_CriminalActivities_MurderAndNonNegligentManslaughter_AsFractionOf_Count_Person
 Number of Muslim boys,indianCensus/Count_Person_Religion_Muslim_YearsUpto6_Male
 Number of Muslim children,indianCensus/Count_Person_Religion_Muslim_YearsUpto6
 Number of Muslim children in rural areas,indianCensus/Count_Person_Religion_Muslim_YearsUpto6_Rural
@@ -2510,7 +2510,7 @@ Number of married couple households with a householder with some college or an a
 Number of married females,Count_Person_Female_MarriedAndNotSeparated
 Number of married foreign born people,Count_Person_15OrMoreYears_MarriedAndNotSeparated_ForeignBorn
 Number of married native people,Count_Person_15OrMoreYears_MarriedAndNotSeparated_Native
-Number of married people,Count_Person_MarriedAndNotSeparated;Count_Person_NowMarried
+Number of married people,Count_Person_MarriedAndNotSeparated
 Number of married people of multi-races,Count_Person_15OrMoreYears_NeverMarried_TwoOrMoreRaces
 Number of married people of one race,Count_Person_15OrMoreYears_MarriedAndNotSeparated_OneRace
 Number of married people of two or more races,Count_Person_15OrMoreYears_MarriedAndNotSeparated_TwoOrMoreRaces
@@ -2520,6 +2520,7 @@ Number of married people who reside in group quarters,Count_Person_MarriedAndNot
 Number of married people who reside in institutionalized group quarters,Count_Person_MarriedAndNotSeparated_ResidesInInstitutionalizedGroupQuarters
 Number of married people who reside in non-institutionalized group quarters,Count_Person_MarriedAndNotSeparated_ResidesInNoninstitutionalizedGroupQuarters
 Number of married people who reside in nursing facilities,Count_Person_MarriedAndNotSeparated_ResidesInNursingFacilities
+"Number of married people, including separated",Count_Person_NowMarried
 Number of married white people,Count_Person_15OrMoreYears_MarriedAndNotSeparated_WhiteAlone
 Number of mobile phone subscriptions per person,Count_Product_MobileCellularSubscription_AsFractionOf_Count_Person
 Number of multi race people with disabilities,Count_Person_WithDisability_TwoOrMoreRaces
@@ -2882,7 +2883,6 @@ People with health insurance split by race,dc/topic/WithHealthInsuranceByRace
 People with high blood pressure,dc/topic/BloodPressure
 People with high cholestrol,dc/topic/Cholesterol
 Percent of area that are burned in land fire,Percent_BurnedArea_FireEvent
-Percent of females commiting intentional homicide,Count_CriminalActivities_MurderAndNonNegligentManslaughter_Female_AsFractionOf_Count_Person_Female
 Percent of forest area that burned,Percent_BurnedArea_FireEvent_Forest
 Percent of forest area that experienced high-severity fire,Percent_BurnedArea_FireEvent_Forest_HighSeverity
 Percent of illiterate people older than 60,Count_Person_60OrMoreYears_Illiterate_AsAFractionOf_Count_Person_60OrMoreYears
@@ -2896,7 +2896,6 @@ Percent of land covered by Permanent Water,LandCoverFraction_PermanentWater
 Percent of land covered by Seasonal Water,LandCoverFraction_SeasonalWater
 Percent of land covered by Shrubland,LandCoverFraction_Shrubland
 Percent of land covered by Snow Ice,LandCoverFraction_SnowIce
-Percent of males commiting intentional homicide,Count_CriminalActivities_MurderAndNonNegligentManslaughter_Male_AsFractionOf_Count_Person_Male
 Percentage of Bcg Immunization Coverage Among 1 Year Old female,WHO/bcgv_Female
 Percentage of Bcg Immunization Coverage Among 1 Year Old in Rural Areas,WHO/bcgv_Rural
 Percentage of Bcg Immunization Coverage Among 1 Year Old in Urban areas,WHO/bcgv_Urban
@@ -4181,7 +4180,6 @@ health in the world,dc/topic/GlobalHealth
 health insurance private type,dc/topic/PrivateHealthInsuranceType
 health insurance public type,dc/topic/PublicHealthInsuranceType
 health of mothers,dc/topic/MaternalHealth
-heart attack,dc/topic/Stroke
 high cholestrol condition,dc/topic/Cholesterol
 high humidity and high heat,dc/topic/WetBulbEvent
 high rainfall,dc/topic/Precipitation
@@ -4419,6 +4417,8 @@ number of males without health insurance,Count_Person_Male_NoHealthInsurance
 number of multi race females living Above Poverty Level in the past 12 months,Count_Person_Female_AbovePovertyLevelInThePast12Months_TwoOrMoreRaces
 number of multi races females living below poverty level in the past 12 months,Count_Person_Female_BelowPovertyLevelInThePast12Months_TwoOrMoreRaces
 number of multi-race males,Count_Person_Male_TwoOrMoreRaces
+number of murders,Count_CriminalActivities_MurderAndNonNegligentManslaughter
+number of murders per capita,Count_CriminalActivities_MurderAndNonNegligentManslaughter_AsFractionOf_Count_Person
 number of native hawaiian or other pacific islander females living Above Poverty Level in the Past 12 months,Count_Person_Female_AbovePovertyLevelInThePast12Months_NativeHawaiianOrOtherPacificIslanderAlone
 number of native hawaiian or other pacific islander females living below poverty level in the past 12 months,Count_Person_Female_BelowPovertyLevelInThePast12Months_NativeHawaiianOrOtherPacificIslanderAlone
 number of never married males aged 15 years or older,Count_Person_Male_NeverMarried
@@ -4632,10 +4632,14 @@ proportion of children aged 5 and under who are overweight,WHO/NUTOVERWEIGHTPREV
 proportion of children aged 6-59 Months with anaemia,WHO/NUTRITION_ANAEMIA_CHILDREN_PREV
 proportion of children with asthma,Percent_Person_Children_WithAsthma
 proportion of females aged 15+ who smoke,Count_Person_15OrMoreYears_Female_Smoking_AsFractionOf_Count_Person_15OrMoreYears_Female
+proportion of females commiting murder,Count_CriminalActivities_MurderAndNonNegligentManslaughter_Female_AsFractionOf_Count_Person_Female
+proportion of females commiting murder and non-negligent manslaughter,Count_CriminalActivities_MurderAndNonNegligentManslaughter_Female_AsFractionOf_Count_Person_Female
 proportion of females who use tobacco,Percent_TobaccoUsing_In_Count_Person_Female
 proportion of females with obesity,dc/4lvmzr1h1ylk1
 proportion of low birth weight,WHO/LBW_PREVALENCE
 proportion of males aged 15+ who smoke,Count_Person_15OrMoreYears_Male_Smoking_AsFractionOf_Count_Person_15OrMoreYears_Male
+proportion of males commiting murder,Count_CriminalActivities_MurderAndNonNegligentManslaughter_Male_AsFractionOf_Count_Person_Male
+proportion of males commiting murder and non-negligent manslaughter,Count_CriminalActivities_MurderAndNonNegligentManslaughter_Male_AsFractionOf_Count_Person_Male
 proportion of males who use tobacco,Percent_TobaccoUsing_In_Count_Person_Male
 proportion of men online,dc/topic/sdg_17.8.1
 proportion of people Who Are Physically Inactive,Percent_Person_PhysicalInactivity
diff --git a/tools/nl/embeddings/input/base/main_topics.csv b/tools/nl/embeddings/input/base/main_topics.csv
index 1745a7402d..2ac9a7bf7f 100644
--- a/tools/nl/embeddings/input/base/main_topics.csv
+++ b/tools/nl/embeddings/input/base/main_topics.csv
@@ -297,7 +297,7 @@ dc/topic/SocialSupport,Social Support;Social Support
 dc/topic/SolarConsumption,Solar Consumption;Solar Consumption
 dc/topic/SolarPotential,Solar Potential;Solar Potential;Solar potential
 dc/topic/Storm,Storm;Storm
-dc/topic/Stroke,Stroke;Stroke;stroke attack;heart attack
+dc/topic/Stroke,Stroke;Stroke;stroke attack
 dc/topic/StrokeFemalePopulationByAge,Female Population With Stroke By Age;Female Population With Stroke By Age
 dc/topic/StrokeMalePopulationByAge,Male Population With Stroke By Age;Male Population With Stroke By Age
 dc/topic/StudentEnrollmentLevels,Student Enrollment Levels;Student Enrollment Levels;enrollement levels of students;number of students enrolled;students currently enrolled
diff --git a/tools/nl/embeddings/input/base/sheets_svs.csv b/tools/nl/embeddings/input/base/sheets_svs.csv
index a28c323a84..88759416b6 100644
--- a/tools/nl/embeddings/input/base/sheets_svs.csv
+++ b/tools/nl/embeddings/input/base/sheets_svs.csv
@@ -1142,10 +1142,10 @@ Count_CriminalActivities_CombinedCrime,Number of crimes
 Count_CriminalActivities_ForcibleRape,Number of Rapes
 Count_CriminalActivities_LarcenyTheft,Number of larceny theft
 Count_CriminalActivities_MotorVehicleTheft,Number of car thefts
-Count_CriminalActivities_MurderAndNonNegligentManslaughter,Number of murders and non-negligent manslaughters
-Count_CriminalActivities_MurderAndNonNegligentManslaughter_AsFractionOf_Count_Person,Number of Murder and Non Negligent Manslaughter per capita
-Count_CriminalActivities_MurderAndNonNegligentManslaughter_Female_AsFractionOf_Count_Person_Female,Percent of females commiting intentional homicide
-Count_CriminalActivities_MurderAndNonNegligentManslaughter_Male_AsFractionOf_Count_Person_Male,Percent of males commiting intentional homicide
+Count_CriminalActivities_MurderAndNonNegligentManslaughter,Number of murders and non-negligent manslaughters;number of murders
+Count_CriminalActivities_MurderAndNonNegligentManslaughter_AsFractionOf_Count_Person,Number of Murder and non-negligent manslaughter per capita;number of murders per capita
+Count_CriminalActivities_MurderAndNonNegligentManslaughter_Female_AsFractionOf_Count_Person_Female,proportion of females commiting murder and non-negligent manslaughter;proportion of females commiting murder
+Count_CriminalActivities_MurderAndNonNegligentManslaughter_Male_AsFractionOf_Count_Person_Male,proportion of males commiting murder and non-negligent manslaughter;proportion of males commiting murder
 Count_CriminalActivities_PropertyCrime,Number of property crime incidents
 Count_CriminalActivities_Robbery,Number of robberies
 Count_CriminalActivities_ViolentCrime,Number of violent crimes