diff --git a/docs/source/release_notes/v1.5.0.rst b/docs/source/release_notes/v1.5.0.rst
index 60b761d..4a17b3c 100644
--- a/docs/source/release_notes/v1.5.0.rst
+++ b/docs/source/release_notes/v1.5.0.rst
@@ -4,14 +4,17 @@ Version 1.5.0
 New Features
 -------------
 
-- Markdown and HTML replies in WebSocketPlatform
-- Chat Widget UI
-- New Processor: UserAdaptationProcessor
-- Reply image in WebSocektPlatform
-- LLM Global and User context
+- New User Interface for the WebSocketPlatform: :doc:`Chat Widget <../wiki/platforms/websocket_platform/chat_widget>`.
+- New Processor: :any:`user-adaptation-processor`
+- New LLM feature: :any:`llm-context`
+- New types of replies included in the WebSocketPlatform:
+
+  - HTML Text
+  - Markdown Text
+  - Images
 
 Improvements
 -------------
 
-- Upgrade Streamlit v1.40.0
-- Typing effect on bot messages in streamlit UI
+- Upgraded Streamlit version to 1.40.0, updating the Streamlit UI with the latest improvements
+- Added typing effect on bot messages in Streamlit UI
diff --git a/docs/source/wiki/core/processors.rst b/docs/source/wiki/core/processors.rst
index 8aa3ce6..52e364f 100644
--- a/docs/source/wiki/core/processors.rst
+++ b/docs/source/wiki/core/processors.rst
@@ -111,7 +111,7 @@ When processed, the recognized language will be stored as a session variable in
 UserAdaptationProcessor
 ~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-The :class:`UserAdaptationProcessor <besser.bot.core.processors.language_detection_processor.UserAdaptationProcessor>`
+The :class:`UserAdaptationProcessor <besser.bot.core.processors.user_adaptation_processor.UserAdaptationProcessor>`
 attempts to adapt the bot's responses based on the user's profile. The user profile can be added using the following call:
 
 .. code:: python
diff --git a/docs/source/wiki/nlp/llm.rst b/docs/source/wiki/nlp/llm.rst
index 88845fd..255ca2b 100644
--- a/docs/source/wiki/nlp/llm.rst
+++ b/docs/source/wiki/nlp/llm.rst
@@ -50,6 +50,8 @@ This LLM can be used within any bot state (in both the body and the fallback bod
 There are plenty of possibilities to take advantage of LLMs in a chatbot. The previous is a very simple use case, but
 we can do more advanced tasks through prompt engineering.
 
+.. _llm-context:
+
 Adding context information to an LLM
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~