Sometimes it's not enough to recognize which flow to trigger. Your bot may also need to extract some piece of information from the input to respond appropriately.  

A typical use case is, picking up the user's order and repeating it, like in this example:

> **User**: I'd like to order a coffee.  
> **Bot**: Ok, what coffee would you like?
> 
> **User**: A espresso, please.  
> **Bot**: Ok, a espresso will be ready for pickup in 5 minutes.

In the following, we will show you how to create a flow that enables users to have this kind of conversation with your bot. These are the steps involved:

*   Add a new flow.
*   Set up a flow variable.
*   Add another output node.
*   Configure an After Match to extract information.
*   Use the information in the output.

![flow layout](//images.ctfassets.net/2vbtnveccz5s/153qPgcgglIsm0yLSczWpK/747c161c7e2e46a67511823534139f3f/flow_layout.PNG)

## Create a new flow

We begin by creating a new flow. Just as previous flows we have built, it will have a trigger and an output node.

1. Create a new flow and call it `User wants to order a coffee`.

#### Populate the trigger

1.  Name the trigger `Order a Coffee`.

Now it is time to populate the trigger:  

2. Copy the following learning examples to your clipboard:
```example-inputs
A small filter coffee, please
Can I get a coffee?
Can I have a coffee, please?
Can I order a coffee
Can I order an espresso?
Can you get me a coffee
Could I get a large macchiato?
Could I have a flat white
Could I order a large americano
Give me a Frappuccino, please
I want a small cappuccino!
I want espresso
I want to order a coffee
I would like a coffee
I would like to order a coffee
I'd like a large espresso
I'd like to order an americano
May I have a filter coffee?
```
3.  Select the trigger, go to the 'Examples' panel on the right, and click where it says 'No Positive Examples'. Then hit __Ctrl + V__ to paste the learning examples. You can see that it worked when the examples appear in the field. Have a look at the video below if you are unsure how to import all examples at once.
4.  Scroll down to the Match section and select the 'Generate' button, this will automatically generate a class trigger.
5.  Your trigger is now configured.

![1-new flow](//videos.ctfassets.net/2vbtnveccz5s/4Vktq1CFKUQw358DBj4le6/a24197e05df5ed75739a97b8f8ae2cfc/1-new_flow.mp4)

#### Populate the output node

In the output node, we want to prompt the user to indicate the desired coffee type in more detail:

1.  Select the output node.
2.  Name the node `Ask for coffee type`.
3.  Go to the 'Answer' panel and paste the following: `Ok, what coffee would you like?`.

![2-populate output](//videos.ctfassets.net/2vbtnveccz5s/2XS1476BsYsjrfRIp87lQI/f7d3f0a47379bbba77ae3bb4fa078275/2-populate_output.mp4)

## Extract information from the user input

So far so good. You now have a flow that triggers when users want to order a coffee and it answers with a question about the coffee type. To be able to pick up the coffee type from the user input, we now need to proceed with the following:

*   Set up a flow variable to store the coffee type.
*   Add an additional output node that will summarize the order including the coffee type.
*   Extract the coffee type on the transition between the two output nodes using an After Match.

### Create a flow variable

The flow variable we create here will later hold the coffee type that the user has mentioned:

1.  In the flow's main window, move to the 'FLOW' tab, and select 'Variables'.
2.  Add a variable and name it `orderedCoffeeType`.
3.  Put `""` in the 'Evaluation Script' field. This initializes the variable with the empty string.

![3-add variable](//videos.ctfassets.net/2vbtnveccz5s/5yllb9chRDPEhyxetXvA4W/9dcec34522c6caaa42506d858ea749d8/3-add_variable.mp4)

### Add an additional output node

The transition between the two output nodes should only be traversed if the user mentions a coffee type. To ensure that, we need to:

1. Click on the Plus icon below the output node, followed up with 'Continue With' and 'Transaction'.
2. Name the transition `User responds with coffee type`.
3. With the transition selected, go to the Match section and click 'Add' and then 'Entity' from the drop-down menu.
4. Enter `COFFEES_SERVED` in the Entity field. This means that Teneo will only continue when the user mentions something which matches the entity.

![4-add output](//videos.ctfassets.net/2vbtnveccz5s/5e9pG5t5jUiW90qazwBnfQ/50af1e3e9f7c12ea5254f8cc8ca4d1f0/4-add_output.mp4)

### Extract information from the entity
We will store the coffee type that the user has mentioned in the flow variable `orderedCoffeeType`, and we will do so using an After Match:

1.  Make sure the `User responds with coffee type` transition is still selected.
2.  In the configuration panel, go to the After Match section, click 'Add', and select 'COFFEES_SERVED' under 'Entity'.
3.  Now click into the 'Entity' field, which will make the 'Add Mapping' button clickable. Click the 'Add Mapping' button.
4.  The first field is the 'Source' field. This denotes the value of the NLU variable of the entity 'COFFEES_SERVED' that we want to store. Select `coffeeType` from the dropdown menu.
5.  The second field is the 'Target' field. This denotes the name of the variable where the extracted value is to be stored. Select `orderedCoffeeType` from the dropdown menu.

![5-extract information](//videos.ctfassets.net/2vbtnveccz5s/5JCELlgJ2UJM46fOzlTuc9/0e3fe5cd434a47fbfbe6054247697782/5-extract_information.mp4)

### Configure the output

Finally, now it's time to edit the output node which will hold the summary of the user's order. Note that we add the newly created variable `orderedCoffeeType` First we have to:

1. Select the output below the transition.
2. Name this output node `Summarize order`.
3. Select the 'Answer' field of the new output node and paste `Ok, a ${orderedCoffeeType} will be ready for pickup in 5 minutes.`.
4. Save the flow and you're done!

![6-configure output](//videos.ctfassets.net/2vbtnveccz5s/2vzazxyhbFqt48aJb3BkEJ/3185e886d8851b4b41f51dd5d1197300/6-configure_output.mp4)

## Test the scenarios

Now it's time to test the flow!

> **User**: I'd like to order a coffee.  
> **Bot**: Ok, what coffee would you like?
> 
> **User**: A cappuccino, please.  
> **Bot**: Ok, a cappuccino will be ready for pickup in 5 minutes.

![7-tryout](//videos.ctfassets.net/2vbtnveccz5s/mYJdU6V8w3p39B00lRRIr/0cff9e3d7d525230bb1639e6841faf71/7-tryout.mp4)

## Test yourself

If you have done the previous [test yourself](/getting-started/create-custom-entities#test-yourself) there should be a working entity for Coffee Sizes. Add that entity here and don't forget to try it in Tryout.


Getting Started - Extract Entities

Hero - Getting started

Getting started

Sometimes it's not enough to recognize which flow to trigger. Your bot may also need to extract some piece of information from the input to respond appropriately.  

A typical use case is picking up the user's order and repeating it, like in this example:

> **User**: I'd like to order a coffee.  
> **Bot**: Ok, what coffee would you like?
> 
> **User**: A cappuccino, please.  
> **Bot**: Ok, a cappuccino will be ready for pickup in 5 minutes.

In the following, we will show you how to create a flow that enables users to have this kind of conversation with your bot. These are the steps involved:

*   Add a new flow.
*   Set up a flow variable.
*   Add another output node.
*   Configure a data action to extract information.
*   Use the information in the output.

![order-a-coffee](//images.ctfassets.net/2vbtnveccz5s/1INVdXZXPeYFiHXvEQzCRV/cc5cab492dbe3ba15f7e786a206ffa8a/order-a-coffee.PNG)

## Create a new flow

We will begin by creating a new flow. Just as previous flows we have built, it will have a trigger and an output node.

1. Click on the 'Create' button followed by 'Create new flow'.
2. Give the flow the name `User wants to order a coffee`.

We now need to create a flow variable. The flow variable will later hold the coffee type that the user has mentioned.

3. Click on the add button besides variables and give the variable the name `orderedCoffeeType`.
4. Put `""` in the 'Variable value' field. This initializes the variable with the empty string.
5. Finally, click on 'Create' to create your flow.

![1-create-the-flow](//videos.ctfassets.net/2vbtnveccz5s/3c5XQfNmO6UN8bvnedcP61/5bc906e42ffdcde22b42b64392ced938/1-create-the-flow.mp4)

Let's proceed by further developing our flow.

### Populate the trigger

1.  Name the trigger `Order a Coffee`.

Now it is time to populate the trigger:  

2. Copy the following learning examples to your clipboard:
* `A small filter coffee, please`
* `Can I get a coffee?`
* `Can I have a coffee, please?`
* `Can I order a coffee`
* `Can I order an espresso?`
* `Can you get me a coffee`
* `Could I get a large macchiato?`
* `Could I have a flat white`
* `Could I order a large americano`
* `Give me a Frappuccino, please`
* `I want a small cappuccino!`
* `I want espresso`
* `I want to order a coffee`
* `I would like a coffee`
* `I would like to order a coffee`
* `I'd like a large espresso`
* `I'd like to order an americano`
* `May I have a filter coffee?`
3.  Select 'Edit' on the trigger and then hit __Ctrl + V__ to paste the learning examples. You can see that it worked when the examples appear in the field. Have a look at the video below if you are unsure how to import all examples at once.
4.  It is now time to generate a Match Requirement. Click on the Plus icon under the trigger, followed by 'Match' and 'Generate a draft'. This will automatically generate a Match Requirement for the trigger.
5.  Your trigger is now configured.

![2-generate-a-match-trigger](//videos.ctfassets.net/2vbtnveccz5s/5lVq6yuqkmzCIVqGqVZv3k/4d8d5a09aa3df1b6b42e4ae510013df6/2-generate-a-match-trigger.mp4)

### Populate the output node

In the output node, we want to prompt the user to indicate the desired coffee type in more detail:

1.  Name the output node `Ask for coffee type`.
2.  Click on 'Edit' and paste the following: `Ok, what coffee would you like?`.

![3-ask-for-coffee-type](//videos.ctfassets.net/2vbtnveccz5s/4RTI8EkUrCAP45Ki3C8UCz/bb99e093f14314f8174b944f2fbee18c/3-ask-for-coffee-type.mp4)

## Extract information from the user input

So far so good. You now have a flow that triggers when users want to order a coffee and answers with a question about the coffee type. To be able to pick up the coffee type from the user input, we now need to proceed with the following:

*   Using After Match, extract the coffee type mentioned by the user. 
*   Add an additional output node that will summarize the order including the coffee type.

### Configure the transition

The transition after the output node should only be traversed if the user mentions a coffee type. To ensure that, we need to:

1.  Click on the Plus icon after the output node.
2.  Select 'Continue with', followed by 'Transaction'. This will create an additional output node.
3.  Select the Plus icon under the user intent.
4.  Click on 'Match', followed by 'Entity'.
5.  Enter `COFFEES_SERVED` in the Entity field. This means that Teneo will only continue when the user mentions something which matches the entity.

![4-add-match-requirement](//videos.ctfassets.net/2vbtnveccz5s/1uHdl6DqY9nOnC4TYCrMfj/97870e04cb1054135c9cda66adf89518/4-add-match-requirement.mp4)

### Extract information from the entity

Finally, we will store the coffee type that the user has mentioned in the flow variable `orderedCoffeeType`, and we will do so using a data action:

1.  Click on the Plus icon under the Match we just created.
2.  Select 'After Match', followed by 'Entity'.
3.  Enter `COFFEES_SERVED` in the text field.
4.  Click the 'Add Variable Mapping' button. This will allow you to extract a value from the Entity to be stored in a variable.
5.  The 'Source' (left) field denotes the value of the NLU variable of the entity 'COFFEES_SERVED' that we want to store. In our case `coffeeType`.
6.  The 'Target' (right) field denotes the name of the variable where the extracted value is to be stored. In our case `orderedCoffeeType`.

![5-after-match](//videos.ctfassets.net/2vbtnveccz5s/2XVAtAUfN8bf1HcWpyIiAq/61eec624a118646462bece58e27baea2/5-after-match.mp4)

### Summarize the order

Now it's time to edit the last output node which will hold the summary of the user's order. This output will name the coffee type mentioned by the user, which we have stored in the variable `orderedCoffeeType`.

1.  Navigate to the last output node.
2.  Name this output node `Summarize order`.
3.  Click on 'Edit' and paste in the following answer to summarize the order: `Ok, a ${orderedCoffeeType} will be ready for pickup in 5 minutes.`.
4.  Finally, save the flow.

![6-save-the-flow](//videos.ctfassets.net/2vbtnveccz5s/4gey5qO6UNVZDnYIYwrPXF/95aa61fc2add18303f6cebc7b349a137/6-save-the-flow.mp4)

## Test the scenarios

Now it's time to test the flow!

> **User**: I'd like to order a coffee.  
> **Bot**: Ok, what coffee would you like?
> 
> **User**: A cappuccino, please.  
> **Bot**: Ok, a cappuccino will be ready for pickup in 5 minutes.

![7-test-in-tryout](//videos.ctfassets.net/2vbtnveccz5s/5FrdtL3HgcLjGhfjSekTaZ/d96f248f2b6257c22f79e66d03187524/7-test-in-tryout.mp4)

## Test yourself

If you have done the previous [test yourself](/getting-started/create-custom-entities#test-yourself) there should be a working entity for Coffee Sizes. Add that entity here and don't forget to try it in Try Out.


Studio Web - Extract Entities

Extract Entities

Analyze your bot

Analyze Log Data

Analyzing sessions

Augmenters

Concepts

Extract values with Augmenters

How To

Metadata

Running custom queries

Counting coffees with Metadata

Reference

Teneo Query Language Cookbook

Teneo Query Language Reference Guide

Teneo Query Language Syntax Overview

Teneo Query Language

Data hierarchy

Event

Property

Session

Transaction

How to

Explore session statistics

Find stuck flows

Generate session logs

Locate and view a session

Make use of skip constraints

Make use of sub queries

Query variables

Troubleshoot the Safetynet

Use relative dates in queries

Query Syntax

Command

Constraint

Meta-parameter

Selection

Transformer

Build your bot

Bot design

Best practices

Data footprint

Encrypting user data in sessions

Flow checklist

Plan your bot

Starting a new Teneo project

Writing good answers

Writing good examples

Conversations

Context restrictions

Flow stack

Greeting message

Listeners

Safetynet

Trigger Ordering

Create a custom order group

Handle ambiguous inputs

Make your bot pro-active

Share information between flows

Use listeners

Flows

Bulk Import

Entities

Junctions

Outputs

Sub-Flows

Transitions

Intent triggers

Variables

Add a script to your flow

Branch at the beginning of a flow

Use TLML Syntax Match

Use a Sub-Flow

Use Bulk Import

Language Understanding

Annotations

Attached scripts

Language conditions

Language objects

Languages

Lexical resources

Libraries

Linguistic Modeling Language

Localization

Match requirements

Used words

Combine Match requirements

Create a solution in your language

Create your own language objects

Find language objects and entities

Localize a bot

Normalize the user's spelling

Optimize language conditions

Recognize plural and singular

Store what the user said

Advanced Condition Coding

Annotations Reference

Condition Syntax Reference

DateTime Handler

Engine Scripting API Reference

Input Processing Path

Language Object Reference

Scripting

Engine scripting API

Groovy basics

Integration manager

Resource file manager

Scripts

Add a Groovy class

Add an integration

Add files to your solution

Annotate user inputs

Anonymize user data

Define a scripted context

Populate output parameters

Store input parameters

Test your bot

Run automated tests

Test your bot with Botium

Dialog Tester

Deploy your bot

Engine API

Versioning and Publishing

Publish your bot

Version Flags

Work with Version Flags

SDK's

Android

JavaScript

Node.js

After Match

Class Manager

Introduction to transitions

Introduction to entities

Deal with Follow-ups

Dialogue and Context Model

Getting started with Teneo

Handle interruptions

Skip conditions

Teneo in 10 minutes

Flows and match requirements

Entities and After Match

Your First Flow

Your First Solution

Optimize your bot

Optimize classes

Improve the balance

Review Inputs

Refine your bot

Debug your bot in Tryout

Use data to improve your bot

Use Teneo's improvement tips

Troubleshooting

My flow doesn't trigger

My flow behaves unexpectedly

I see warnings in Tryout

Suggestions

root

Table of Contents