diff --git a/www/docs/api-reference/indexing-apis/file-upload/file_upload.md b/www/docs/api-reference/indexing-apis/file-upload/file_upload.md
index 21e87192..862f9236 100644
--- a/www/docs/api-reference/indexing-apis/file-upload/file_upload.md
+++ b/www/docs/api-reference/indexing-apis/file-upload/file_upload.md
@@ -57,8 +57,8 @@ following parts:
   metadata to be associated with the extracted document.
 - `chunking_strategy` (Optional) Specifies whether to split the document into 
   chunks during ingestion. If not set, the platform defaults to sentence-based 
-  chunking, where each chunk contains one full sentence. Set the `type` as 
-  `max_chars_chunking_strategy` and then specify the `max_chars_per_chunk` to 
+  chunking, where each chunk contains typically one full sentence. Set the `type` 
+  as `max_chars_chunking_strategy` and then specify the `max_chars_per_chunk` to 
   the number of characters per chunk like `512` or `1024`. Smaller chunks may improve granularity 
   but can lead to excessive latency, especially in applications with high 
   document volumes or large corpora.
diff --git a/www/docs/api-reference/indexing-apis/indexing.md b/www/docs/api-reference/indexing-apis/indexing.md
index 7e7d4e93..5cb44d4d 100644
--- a/www/docs/api-reference/indexing-apis/indexing.md
+++ b/www/docs/api-reference/indexing-apis/indexing.md
@@ -63,7 +63,7 @@ sum of both values.
 
 ### Structured document chunking
 
-By default, Vectara uses sentence-based chunking, where each chunk consists of 
+By default, Vectara uses sentence-based chunking, where each chunk typically contains 
 one complete sentence. This strategy works well but can lead to higher 
 retrieval latency because of the increased number of chunks. Alternatively, 
 you can use character-based chunking to make the chunks larger.
diff --git a/www/docs/console-ui/manage_documents.md b/www/docs/console-ui/manage_documents.md
index 7a21b684..4a590554 100644
--- a/www/docs/console-ui/manage_documents.md
+++ b/www/docs/console-ui/manage_documents.md
@@ -44,8 +44,8 @@ shows the Text, Context, and Metadata.
 
 ![View Document Parts](/img/parts_tab.png)
 
-Select the **Tables** tab to view information about extracted tables, including 
+Select the **Tables** tab to view information about ingested tables, including 
 their ID, Title, Rows, and Description. You can also select **View Table** in 
-the Table column.
+the Table column to view the rendered table.
 
 ![View Table Tab](/img/tables_tab.png)
diff --git a/www/docs/learn/querying-table-data.md b/www/docs/learn/querying-table-data.md
index 11c78901..4f6f3b9b 100644
--- a/www/docs/learn/querying-table-data.md
+++ b/www/docs/learn/querying-table-data.md
@@ -130,9 +130,9 @@ table-specific metadata that’s shaped like this:
 * **row_num:** This value is a number if the search result is for a specific row 
   of the table.
 
-When you open a corpus in the UI and select the **Data** tab, you can then 
-select the **Tables** tab to view the ingested table data as well as view the 
-rendered table. For more details, see [Manage Documents](/docs/console-ui/manage-documents).
+When you open a corpus in the UI and select the **Data** tab, you can click on 
+**each uploaded document** and select the **Tables** tab to view the ingested table 
+data as well as view the rendered table. For more details, see [Manage Documents](/docs/console-ui/manage-documents).
 
 ## Table examples
 
diff --git a/www/docs/learn/select-ideal-indexing-api.md b/www/docs/learn/select-ideal-indexing-api.md
index 6893631b..f4821469 100644
--- a/www/docs/learn/select-ideal-indexing-api.md
+++ b/www/docs/learn/select-ideal-indexing-api.md
@@ -110,8 +110,9 @@ the trade-offs between granularity and latency.
 ### Default chunking
 
 By default, the platform uses sentence-based chunking, where each chunk 
-contains one complete sentence. This strategy can lead to higher retrieval 
-latency for large documents due to the increased number of chunks created.
+typically contains one complete sentence. This strategy can lead to higher 
+retrieval latency for large documents due to the increased number of chunks 
+created.
 
 ### Fixed-size chunking