DOC: Miscellaneous UI and editorial updates (#7324)

### What problem does this PR solve?



### Type of change


- [x] Documentation Update

docs/guides/dataset/run_retrieval_test.md

@@ -11,7 +11,7 @@ Conduct a retrieval test on your knowledge base to check whether the intended ch
 
 After your files are uploaded and parsed, it is recommended that you run a retrieval test before proceeding with the chat assistant configuration. Running a retrieval test is *not* an unnecessary or superfluous step at all! Just like fine-tuning a precision instrument, RAGFlow requires careful tuning to deliver optimal question answering performance. Your knowledge base settings, chat assistant configurations, and the specified large and small models can all significantly impact the final results. Running a retrieval test verifies whether the intended chunks can be recovered, allowing you to quickly identify areas for improvement or pinpoint any issue that needs addressing. For instance, when debugging your question answering system, if you know that the correct chunks can be retrieved, you can focus your efforts elsewhere. For example, in issue [#5627](https://github.com/infiniflow/ragflow/issues/5627), the problem was found to be due to the LLM's limitations.
 
-During a retrieval test, chunks created from your specified chunk method are retrieved using a hybrid search. This search combines weighted keyword similarity with either weighted vector cosine similarity or a weighted reranking score, depending on your settings:
+During a retrieval test, chunks created from your specified chunking method are retrieved using a hybrid search. This search combines weighted keyword similarity with either weighted vector cosine similarity or a weighted reranking score, depending on your settings:
 
 - If no rerank model is selected, weighted keyword similarity will be combined with weighted vector cosine similarity.
 - If a rerank model is selected, weighted keyword similarity will be combined with weighted vector reranking score.