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  1. Docs
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  4. How to use Patterns for Intents & Entities

How to use Patterns for Intents & Entities

Using patterns can help to improve NLP interpreter accuracy.

In this document, we will elaborate on the various pattern syntax and how they can be used in intent detection and entity extraction.

Things to Remember:

  • Patterns are to be used as a last resort, only for cases where ML engine cannot be used. Examples of such cases would be to train bot in recognising idiomatic utterances, command like utterances.
  • Patterns are evaluated in the order of their listing. Once a match is found the rest of the patterns are not evaluated. So ensure when adding patterns to add in the order of most restrictive to least restrictive.
  • Only one wildcard (*) is allowed in a pattern.
  • While most of the features are supported in all languages, there are some exceptions, see here for more details.
The following are some general guideline for creating intent patterns:
  • Use a minimum of 3 words.
  • Use words in their canonical forms (i.e. infinitive verbs, singular nouns).
  • Use lowercase both for words and their synonyms.
  • Use the US spelling of words (i.e. normalize instead of normalise).
  • Avoid using determiners and pronouns (the, a, my, that).
  • Avoid using digits.
  • Avoid using entity values in defining a task pattern.
  • Don’t use elision (i.e. what’s ).
  • Don’t use special characters such as () & / \ $ [ ] + *.
  • Don’t use punctuation such as – , . ! ? ‘ “.

Patterns for Intent Detection

Following is a list of pattern syntax, along with examples, that can be configured for intent detection.

Pattern Description Pattern Examples
word1 word2 … wordn This mandates all the words defined to be available in the user utterance in the same consecutive order with upto 3 (language specific) additional words allowed between any two consecutive words mentioned in the pattern and infinite number of words before and after those specified set of words.
Sample Pattern transfer fund
Utterance Match – “can you please transfer funds from my account
– “can you please transfer some funds from my account
– “transfer funds
Utterance not Matching – “i want to transfer
– “can i transfer some significant amount of monetary funds
– “i want to do fund transfer
word1_word2 Enforce phrase, no additional words allowed in between word1 and word2. This is to ensure a sequence of tokens are read as a phrase. Usage restricted to words, concepts not allowed.
Note: There should be no space between the word1, word2 and _. Also be aware that “_word1” is to ensure that the word1 in the user utterance is not marked as Used Up by the platform and is to be considered for entity extraction. This is useful when entity words are used in the intent pattern.
Sample Pattern transfer_fund
Utterance Match can you help me transfer funds
Utterance not Matching can you please transfer some funds from my account
word1 * word2 0 to infinite number of additional words between the specified words/phrases
Sample Pattern transfer * fund
Utterance Match – “can you please transfer some funds from my account
– “can you help me transfer funds
Utterance not Matching i want to transfer
word1 *n word2 Exactly n number of additional words between the specified words/phrases
Sample Pattern transfer *2 fund
Utterance Match – “can you help me transfer some significant funds from my account
Utterance not Matching – “i want to transfer
– “can you please transfer some funds from my account
– “can you help me transfer some significant amount of funds
word1 *0 word2 To disable wildcards between two tokens. Similar to the underscore between two words but can be used between two concepts or within [  ], {  } groups.
(available 7.1 onwards)
Sample Pattern transfer *0 fund
Utterance Match – “can you please transfer funds from my account
– “can you help me transfer funds
Utterance not Matching i want to transfer some funds
word1 < word2 Indicates the match for word2 should start from the beginning of a sentence. It is useful especially when the word2 appears in the middle of the utterance.
Add a space after the angular bracket
Sample Pattern transfer < fund
Utterance Match – “want to transfer funds
– “i want to initiate fund transfer
Utterance not Matching i want to transfer
word1 > word2 Indicates the end of the sentence and no words are allowed after it.
Add a space before closing the angular bracket
Sample Pattern transfer * fund >
Utterance Match – “transfer funds
– “transfer few funds
Utterance not Matching transfer funds today
!abc Indicates the word/concept “abc” should not exist anywhere in the user utterance after this token
No space between ! and word/concept
Sample Pattern – “!status transfer fund
– “transfer !status fund
– “transfer fund !status
Utterance Match i want to transfer funds
Utterance not Matching – “what is the status of my fund transfer
– “i want to find my fund transfer status
!!abc The very next word/concept should not be “abc”
No space between !! and word/concept
Sample Pattern transfer fund !!status
Utterance Match – “i want to transfer funds
– “what is the status of my fund transfer
– “i want to find my fund transfer from yesterday’s status
Utterance not Matching i want to find my fund transfer status
[ … ] Used to define a group of words/concepts and the match should be against exactly one of the group declared in [ ]. Be aware that when a match is found the rest of the group is ignored, so order the words accordingly.
Note: the parentheses should not be clubbed with the word, i.e maintain a space between the parenthesis and the adjacent word.
Due to the difficulty in maintaining and tracking, it is recommended you use concept instead of this pattern. This pattern also has detrimental effect on the bot performance.
Sample Pattern transfer [ funds amount cash ]
Utterance Match – “transfer money
– “can i transfer some cash
– “i want to transfer funds
Utterance not Matching transfer dollars
{ … } Used to define a optional group or words/concepts and the match would be against zero or one of the words/patterns declared in { }. Be aware that when a match is found rest of the group is ignored, so order the words accordingly.
Note: the parentheses should not be clubbed with the word, i.e maintain a space between the parenthesis and the adjacent word.
Sample Pattern transfer { some few my } fund
Utterance Match – “how do i transfer funds
– “can i transfer some funds
Utterance not Matching i want to transfer
( … ) contain a pattern i.e when a pattern or part of a pattern is enclosed in these parentheses, we treat it as a pattern unlike [ ] and { }.
This is the default setting i.e. when a pattern word1 word2 it is treated as ( word1 word2 )
Commonly used explicitly to define sub pattern inside [ ] or { }
Sample Pattern ( transfer fund )
Utterance Match transfer funds from my account
Utterance not Matching i would like to initiate fund transfer
<< … >> Used to find words in any order
Due to the risk of running into false positives, you are advised not to use this pattern.
Sample Pattern << transfer fund >>
Utterance Match – “transfer funds from my account
– “i would like to initiate fund transfer
Utterance not Matching i want to transfer
‘word1 If you quote words or use words that are not in canonical form, the system will restrict itself to what you used in the pattern
Sample Pattern ‘like to transfer fund
Utterance Match I would like to ransfer funds from my account
Utterance not Matching I really liked transfer funds process
word1~concept2
~concept1~concept2
(from ver8.0)
A word (word1) or concept (concept1) can be matched only if it is also a member of another concept (concept2). The most common usage of this is through the system concepts that are dynamically added for each POS tag.
Sample Pattern schedule~verb
Utterance Match schedule a meeting
Utterance not Matching show my schedule

Pattern Operators

  • AND: ( X Y ): An ordered relationship of words in sequence. This is the default setting. i.e. when you specify a pattern as cancel order it is the same as (cancel order).
    For example, (Cancel Order) matches Cancel my phone order but doesn’t match I have a pending order for an iPhone X, can I cancel. Bot Builder tool uses patterns with increasing numbers of wildcards between words (up to 3 for an intent). So a pattern of Cancel Order can match:
    • cancel order
    • cancel my order
    • cancel that last order
    • cancel last weeks big order
  • OR: [X Y Z]: Any of these can be interchangeably used in the user utterance. For example, ([get make] me [food drink dessert]) will match any of the below utterances:
    • Get me food
    • Make me a drink
    • Get me a drink
    • Get me a dessert
    • Make me some quick food
  • NOT: !X: Words that should not appear in the user utterance for an intent match. For example, (!forecast) is marked as a pattern for intent named Get current weather and the bot supports another intent called Get 3-day weather forecast.
    • User utterance: Planning a trip to California get me the forecast
      • will not match Get current weather
      • will match Get 3-day weather forecast
        Note that the !word means not after this point. So (!forecast the weather) and (get the weather !forecast) are different. The utterance get the forecast for the weather matches the second but not the first.
  • Optional: {X}: For example, {phone} If the user utterance is Get me a phone number or get me a number the platform will treat it equally.
  • Enforce Phrase: X_Y: To enforce occurrence of the phrase as is in the user utterance, without any words in between. For example, transfer_funds. The utterance transfer funds or I want to transfer funds will match but not Can I transfer some funds.
  • Concepts: ~: Platform has a large set of inbuilt concepts that developers can use to define a pattern. For example, (I [like love] ~world_country) will match
    • I like India
    • I love traveling to Australia
    • I would like to visit an African country
  • Unordered: <<, >>: Used to find words in any order. For example, <<Cancel Order>> matches Cancel my phone order and also I have a pending order for an iPhone X, can I cancel
  • Start/End of Statement: <, >: For example, ( transfer fund > ) will match I want to transfer funds but will not match transfer funds today.
  • Quote: ‘ –: If you quote words or use words that are not in canonical form, the system will restrict itself to what you used in the pattern. For example, (like to transfer funds) This matches I would like to transfer funds from my account but not I really liked transfer funds process.

Negative Patterns

Negative Patterns can be used to eliminate intents detected in the presence of a phrase. This will help filter the matched intents for false positives.

User Utterance: “I was transferring funds when I got network failure error”
Intent DetectedTransfer Funds
Intended IntentRegister Complaint

Add a Negative Pattern (network failure) (error) (technical issue) for the intent Transfer Funds
User Utterance: “I was transferring funds when I got network failure error”
or “I was transferring funds when I faced a technical issue”
or “I got an error during transfer funds process.”
Intent RejectedTransfer Funds
Intent Triggered: Register Complaint

Patterns for Entity Extraction

Patterns can be used to identify the values for entities in user utterance based upon their position and occurrence in user utterance.

Intent patterns operators like {…}, […], !, ~concepts can be used for entity extraction. The following are some use cases how the patterns can be applied.

Every entity pattern has to include a * (of some form) to represent where the platform should look for an entity value.

Continuing with the Banking Bot example with Transfer Funds intent. This intent needs two entities – ToAccount and FromAccount. We will see how to achieve this.

Pattern 1: word1 * word2

This can be used as a positional wildcard that indicates the expected position of the entity.
Pattern for ToAccount entityto * from
User UtteranceTransfer funds to ABC123 from my account.
Entity ExtractedToAccount = ABC123
User Utterance not resulting in entity extraction: “transfer funds for ABC123 from my account”

Pattern 2: word1 *n

This can be used as a positional wildcard * that indicates the expected position of the entity based upon the number of words after the specified word1. That is, n words after the word1 are to be considered for the entity, if n words are not present then look for the next occurence of word1.
Pattern for ToAccount entity: from *2
User UtteranceTransfer funds to ABC123 from my account.
Entity Extracted: FromAccount = my account
User Utterance: Transfer funds to ABC123 from XYZ321 that is from my account.
Entity Extracted
: FromAccount = my account
User Utterance not resulting in entity extraction
: “transfer funds to  ABC123 using my account”

Extension to Pattern 2: word1 *~n

Similar to above (pattern 2) but extracts up to n number, if that number of words are available. Note that entities need to extract something so *~1 is really the same as *1.

Pattern 3: a combination of word1 * word2 and word3 *n

This can be used as a combination of patterns for the likely location in the user utterance that the entity value could be found and the number of words contributing to the entity.
Pattern for ToAccount entity“to * from” and “from to *1”
Pattern for FromAccount entity: “from * to” and “to from *2”
User UtteranceTransfer funds to ABC123 from my account.
                       or Transfer funds from my account to ABC123.
Entity ExtractedToAccount = ABC123 and FromAccount = my account
User Utterance not resulting in entity extraction: “transfer funds for ABC123 using my account”

Pattern 4: [ word1 word2 ] *

This can be for patterns using a group of words or concepts of which at least one should be present in the utterance. The order within the group is important (see above in intent detection for details).
Pattern for ToAccount entity“to * [ using from ]” and “[ using from ] to *1”
Pattern for FromAccount entity: “[ using from ] * to” and “to [ using from ] *”
User UtteranceTransfer funds to ABC123 from my account.
                       or Transfer funds using my account to ABC123.
Entity ExtractedToAccount = ABC123 and FromAccount = my account
User Utterance not resulting in entity extraction: “transfer funds for ABC123 using my account”

Pattern 5: ~CustomConcept *

This can be for using concepts. You can create your own custom concepts and use them to define patterns.
Pattern for ToAccount entity“to * from” and “from to *”
Pattern for FromAccount entity: “~in * to” and “to ~in *”
Custom Concept: ~in(using) (from)
User UtteranceTransfer funds to ABC123 using my account.
                       or Transfer funds from my account to ABC123.
Entity ExtractedToAccount = ABC123 and FromAccount = my account
User Utterance not resulting in entity extraction: “transfer funds to ABC123 of my account

Pattern 6: ~intent

Useful in entity patterns and custom entities
Words that are used in the intent identification are dynamically marked with the ~intent concept. This can then be used as an anchor or reference point for some entity patterns.
Sample Pattern“~intent~meeting~plural
User Utterance not resulting in entity extraction: show my meetings.
User Utterance might mark the entity: “schedule a presentation called Meeting the Sales Goals

Pattern 7: $currentEntity

Useful in delaying the evaluation of a pattern until the entity is actually processed. Normally entity patterns are evaluated when a dialog starts and on new input to see if any words need to be protected until that entity is processed. This might not always desirable, especially for strings.
Pattern“$currentEntity=TaskTitle ‘called *
The above rule will result in evaluating the pattern when the dialog flow has reached the TaskTitle node.

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