typo fixes

.typo-ci.yml

@@ -172,5 +172,6 @@ excluded_words:
   - crfentityextractor
   - Comerica
   - entitysynonymmapper
+  - memoizationpolicy
 
 spellcheck_filenames: false

docs/docs/business-logic.mdx

@@ -4,7 +4,7 @@ sidebar_label: Handling Business Logic
 title: Handling Business Logic
 ---
 
-Conversational assistants often suppor user goals that involve collecting required information
+Conversational assistants often support user goals that involve collecting required information
 from the user before doing something for them. For example, a restaurant search bot would need to gather a few pieces of information
 about the user's preferences to find them 
 a suitable restaurant:
@@ -309,6 +309,6 @@ example above, this is a summary of what you'll need to do:
 
 To try out your newly defined form, retrain the bot and start `rasa shell`.
 If your final action is a custom action, you'll need to start the action server 
-in a seperate terminal when running `rasa shell`. If you're using `DucklingEntityExtractor` to extract
+in a separate terminal when running `rasa shell`. If you're using `DucklingEntityExtractor` to extract
 entities, you'll need to start Duckling in the background as well
 (see the [instructions for running Duckling](entity-extractors.mdx#ducklingentityextractor)).

docs/docs/chitchat-faqs.mdx

@@ -80,7 +80,7 @@ pipeline:
 ```
 
 By default, the `ResponseSelector` will build a single retrieval model for all retrieval intents.
-If you want to retrieve responses for FAQs and chitchat seperately, you can use multiple `ResponseSelector` components 
+If you want to retrieve responses for FAQs and chitchat separately, you can use multiple `ResponseSelector` components 
 and specify the `retrieval_intent` key, for example:
 
 ```rasa-yaml
@@ -141,7 +141,7 @@ nlu:
       - what language does rasa support?
       - which language do you support?
       - which languages supports rasa
-      - can I use rasa also for another laguage?
+      - can I use rasa also for another language?
       - languages supported
   - intent: faq/ask_rasax
     examples: |

docs/docs/command-line-interface.mdx

@@ -250,7 +250,7 @@ the following arguments:
 ```
 
 This command will attempt to keep the proportions of intents the same in train and test.
-If you have NLG data for retrieval actions, this will be saved to seperate files:
+If you have NLG data for retrieval actions, this will be saved to separate files:
 
 ```bash
 ls train_test_split

docs/docs/contextual-conversations.mdx

@@ -112,7 +112,7 @@ policies:
 
 You want to make sure `max_history` is set high enough
 to account for the most context your assistant will need to make an accurate 
-prediction about awhat to do next.
+prediction about what to do next.
 For more details see the docs on [conversation featurization](policies.mdx#conversationfeaturization).
 
 ### `TEDPolicy`

docs/docs/fallback-handoff.mdx

@@ -231,7 +231,7 @@ starterpacks.
 You'll need to define rules for fallback and out-of-scope situations.
 You'll only need NLU training data for out-of-scope intents. 
 For human handoff, no training data is needed unless you want 
-a seperate rule for handing off to a human vs. Two-Stage-Fallback,
+a separate rule for handing off to a human vs. Two-Stage-Fallback,
 or if you want to create a `human_handoff` intent that can be predicted directly.
 
 ### NLU Training Data
@@ -278,20 +278,13 @@ rules:
 Using [Rules](./rules.mdx) or [Stories](./stories.mdx) you can implement any desired
 fallback behavior.
 
-<<<<<<< HEAD
-* `data/nlu.yml`:
-=======
 #### Rules for Two-Stage Fallback
->>>>>>> 9a6687ebb2b... Conversation patterns
 
 To use the `Two-Stage-Fallback` for messages with low NLU confidence, add the
 following [Rule](./rules.mdx) to your training data. This rule will make sure that the
 `Two-Stage-Fallback` will be activated whenever a message is received with
 low classification confidence.
 
-<<<<<<< HEAD
-* `data/stories.yml`:
-=======
 ```yaml
 rules:
 - rule: Implementation of the Two-Stage-Fallback
@@ -300,7 +293,6 @@ rules:
   - action: two_stage_fallback
   - form: two_stage_fallback
 ```
->>>>>>> 9a6687ebb2b... Conversation patterns
 
 
 #### Rules for out-of-scope requests