diff --git a/_opensearch/query-dsl/text-analyzers.md b/_opensearch/query-dsl/text-analyzers.md
index e35090c6..98873218 100644
--- a/_opensearch/query-dsl/text-analyzers.md
+++ b/_opensearch/query-dsl/text-analyzers.md
@@ -16,23 +16,24 @@ OpenSearch provides several text analyzers to convert your structured text into
 
 OpenSearch supports the following text analyzers:
 
-1. **Standard analyzer** – parses strings into terms at word boundaries per the Unicode text segmentation algorithm. It removes most, but not all punctuation. It converts strings to lowercase. You can remove stop words if you turn on that option, but it does not remove stop words by default.
-1. **Simple analyzer** – converts strings to lowercase, and removes non-letter characters when it splits a string into tokens on any non-letter character.
-1. **Whitespace analyzer** – parses strings into terms between each whitespace.
-1. **Stop analyzer** – Converts strings to lowercase and removes non-letter characters by splitting strings into tokens at each non-letter character. It also removes stop words (e.g. "but," or "this") from strings.
-1. **Keyword analyzer** – receives a string as input and outputs the entire string as one term.
-1. **Pattern analyzer** – splits strings into terms using regular expressions and supports converting strings to lowercase. It also supports removing stop words.
-1. **Language analyzer** – provides analyzers specific to multiple languages.
-1. **Fingerprint analyzer** – creates a fingerprint to use as a duplicate detector.
+1. **Standard analyzer** – Parses strings into terms at word boundaries per the Unicode text segmentation algorithm. It removes most, but not all, punctuation. It converts strings to lowercase. You can remove stop words if you turn on that option, but it does not remove stop words by default.
+1. **Simple analyzer** – Converts strings to lowercase and removes non-letter characters when it splits a string into tokens on any non-letter character.
+1. **Whitespace analyzer** – Parses strings into terms between each whitespace.
+1. **Stop analyzer** – Converts strings to lowercase and removes non-letter characters by splitting strings into tokens at each non-letter character. It also removes stop words (e.g., "but" or "this") from strings.
+1. **Keyword analyzer** – Receives a string as input and outputs the entire string as one term.
+1. **Pattern analyzer** – Splits strings into terms using regular expressions and supports converting strings to lowercase. It also supports removing stop words.
+1. **Language analyzer** – Provides analyzers specific to multiple languages.
+1. **Fingerprint analyzer** – Creates a fingerprint to use as a duplicate detector.
+
+The full specialized text analyzers reference is in progress and will be published soon.
 
-The full specialized text analyzers reference is in-progress and will be published soon.
 {: .note }
 
 ## How to use text analyzers
 
-If you want to use a text analyzer, specify the name of the analyzer for the `analyzer` field: standard, simple, whitespace, stop, keyword, pattern, fingerprint, and language.
+If you want to use a text analyzer, specify the name of the analyzer for the `analyzer` field: standard, simple, whitespace, stop, keyword, pattern, fingerprint, or language.
 
-Each analyzer consists of one tokenizer and zero or more token filters. Different analyzers have different character filters, tokenizers and token filters. To pre-process the string before the tokenizer is applied, you can use one or more character filters.
+Each analyzer consists of one tokenizer and zero or more token filters. Different analyzers have different character filters, tokenizers, and token filters. To pre-process the string before the tokenizer is applied, you can use one or more character filters.
 
 #### Example: Specify the standard analyzer in a simple query