diff --git a/README.md b/README.md
index 933bb0c..f4507ba 100644
--- a/README.md
+++ b/README.md
@@ -117,7 +117,7 @@ Each `.jsonl` file contains one JSON object per line. See `data/chunks/delan_pro
 
 | JSON field | SQL column | Notes |
 |------------|------------|-------|
-| `chunk_id` | `chunk_id` | Primary key |
+| `chunk_id` | `label_chunk_id` | Primary key |
 | `product_id` | `product_id` | Foreign key to `products` |
 | `product_name` | `product_name` | |
 | `target_crops` | `target_crops` | Stored as JSON string via `json.dumps()` |
diff --git a/ingest.py b/ingest.py
index 67c6bf4..90821db 100644
--- a/ingest.py
+++ b/ingest.py
@@ -47,6 +47,7 @@ DEFAULT_CHUNKS_DIR = Path("data/chunks")
 # re-ingesting the same product always maps to the same object.
 WEAVIATE_UUID_NAMESPACE = uuid.UUID("1b7e2c3a-4f5d-4a8b-9c1e-6d2f3a8b9c0d")
 
+# JSON keys for array-valued profile fields. ``frac_groups`` is stored in SQL as ``frac_codes``.
 ARRAY_FIELDS = (
     "active_ingredients",
     "frac_groups",
@@ -75,14 +76,15 @@ USE_FIELDS = (
     "growth_stage_end",
 )
 
-CHUNK_INSERT_COLUMNS = (
-    "chunk_id",
-    "product_id",
-    "product_name",
-    "target_crops",
-    "target_diseases",
-    "chunk_type",
-    "chunk_text",
+# (SQL column, JSON key). JSON ``chunk_id`` is stored as ``label_chunk_id``.
+CHUNK_COLUMN_SOURCES = (
+    ("label_chunk_id", "chunk_id"),
+    ("product_id", "product_id"),
+    ("product_name", "product_name"),
+    ("target_crops", "target_crops"),
+    ("target_diseases", "target_diseases"),
+    ("chunk_type", "chunk_type"),
+    ("chunk_text", "chunk_text"),
 )
 
 CHUNK_ARRAY_FIELDS = ("target_crops", "target_diseases")
@@ -338,13 +340,13 @@ def upsert_product(cursor: pyodbc.Cursor, profile: Dict[str, Any]) -> None:
             SET product_name = ?,
                 registration_number = ?,
                 manufacturer = ?,
-                organic_certified = ?,
+                is_organic_certified = ?,
                 systemicity = ?,
-                preventive_action = ?,
-                curative_action = ?,
-                eradicant_action = ?,
+                has_preventive_action = ?,
+                has_curative_action = ?,
+                has_eradicant_action = ?,
                 active_ingredients = ?,
-                frac_groups = ?,
+                frac_codes = ?,
                 target_crops = ?,
                 target_diseases = ?,
                 action_type = ?
@@ -352,8 +354,8 @@ def upsert_product(cursor: pyodbc.Cursor, profile: Dict[str, Any]) -> None:
         ELSE
             INSERT INTO products (
                 product_id, product_name, registration_number, manufacturer,
-                organic_certified, systemicity, preventive_action, curative_action,
-                eradicant_action, active_ingredients, frac_groups, target_crops,
+                is_organic_certified, systemicity, has_preventive_action, has_curative_action,
+                has_eradicant_action, active_ingredients, frac_codes, target_crops,
                 target_diseases, action_type
             )
             VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
@@ -405,11 +407,11 @@ def replace_uses(cursor: pyodbc.Cursor, profile: Dict[str, Any]) -> None:
 def chunk_insert_values(chunk: Dict[str, Any]) -> tuple[Any, ...]:
     """Build parameterized insert values for a single label chunk row."""
     values: list[Any] = []
-    for column in CHUNK_INSERT_COLUMNS:
-        if column in CHUNK_ARRAY_FIELDS:
-            values.append(json.dumps(chunk.get(column, [])))
+    for _column, source_key in CHUNK_COLUMN_SOURCES:
+        if source_key in CHUNK_ARRAY_FIELDS:
+            values.append(json.dumps(chunk.get(source_key, [])))
         else:
-            values.append(chunk.get(column))
+            values.append(chunk.get(source_key))
     return tuple(values)
 
 
@@ -421,11 +423,12 @@ def replace_label_chunks(
     """Replace all label-chunk rows for a product with the provided set."""
     cursor.execute("DELETE FROM label_chunks WHERE product_id = ?", product_id)
 
+    insert_columns = [column for column, _source_key in CHUNK_COLUMN_SOURCES]
     insert_sql = f"""
         INSERT INTO label_chunks (
-            {", ".join(CHUNK_INSERT_COLUMNS)}
+            {", ".join(insert_columns)}
         )
-        VALUES ({", ".join(["?"] * len(CHUNK_INSERT_COLUMNS))})
+        VALUES ({", ".join(["?"] * len(insert_columns))})
     """
 
     for chunk in chunks: