# Match entities
A match entity can be detected anywhere in the conversation, meaning it is context-independent.
## Detect information anywhere
Entities can always be asked inside a [Collect input](/buildabot/flow-logic/dialog-state/user-input-bot-dialog.md) block, but **match entities** can be detected anywhere in the conversation, which means they will skip the **Collect input** block in your flow. This would result in a conversation like this one:
Because you predefined the package number as a match entity, the bot was able to pick up on it in the user's expression, therefore skipping the Collect input block asking for it. The result is a much better user experience and a seemingly smarter bot 😉
## Match text or patterns
Match entities have 2 options:
* to match a [text](#match-text)
* to match a [pattern](#match-pattern)
Match entities example.
{% hint style="warning" %}
Note that match entities are context-independent, meaning that they can be detected at any place in the conversation. Therefore, they are very different from [contextual entities ](/nlp/natural-language-processing-nlp/detect-information-with-entities/contextual-entities.md)which are context-dependent and can be detected only at certain places inside the conversation.
{% endhint %}
### Add a match text entity
A match text entity will be detected when what the user says matches a value in a pre-defined list.
To add a Match text entity:
1. From the [Entities](/navigation/natural-language-processing-nlp/synonym-entities.md) tab, click on the **Add match entity** button.
2. Select **Match text**.
3. Enter an **Entity name**.
4. Enter different **Entity values**.
5. If you want to, add [**Synonyms**](#synonyms-in-match-text-entities) to these values by typing them in the field then clicking `Enter` on your keyboard.
Synonyms in match text entities
For each value of a matched text, you can add a synonym that will be detected as the original value. Synonyms allow you to add alternatives to entities that are assigned to the same value.
For example:
*I want to go to Brussels*
*I want to go to Bruxelles*
The meaning of the two expressions above is exactly the same, but you want to convert *Bruxelles* to *Brussels* so your bot can work with one and the same value.
Note that match entities are case insensitive, so there's no need to add capitalized synonyms.
Add a match text entity.
6. Click on **Create entity**.
When a user says "I want to know more about the **Premium** pack", the match entity **@product** will be recognized and saved with the value "Premium".
### Add a match pattern entity
A match pattern entity will be detected when what the user says matches a certain regular pattern.
To add a match pattern entity:
1. From the [Entities](/navigation/natural-language-processing-nlp/synonym-entities.md) tab, click on the **Add match entity** button.
2. Select **Match pattern**.
3. Add an **Entity name**.
4. Add a regular expression under **Pattern**.
Regular expressions in match pattern entities
The pattern that you fill in match pattern entities should be written as a regular expression (RegEx) Python style. For more information check .
For example: you have defined **@customer\_ID** as a match entity, and have provided the following regex pattern: `[a-z]{5}[0-9]{2}`. This means that when a users says "My customer ID is terwf33" – which consists of 5 letters and 2 numbers – it is saved as the match entity **@customer\_ID** with the value "terwf33".
Add a match pattern entity.
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