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2. Java and other programming.
3. languages.
4. HTML and XML.
5. Interactive data language and object definition language.
6. SQL and other database languages.
7. Modeling languages.
8. Scripting languages.
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2.  If source text does not match against format error is thrown or returned. If source text does not match against format, an error is thrown or returned.
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Parsing

What is parsing?

Parsing is the process of analyzing a string of symbols, either in natural language, computer languages, or data structures, conforming to formal grammar rules.

Data parsing

Data parsing is a method where one string of data gets converted into a different type of data. So let’s say you receive your data in raw HTML. A parser will take the said HTML and transform it into a more readable data format easily read and understood.

The 3 types of parsing

Tree type is a common and standard choice for XML parsing, HTML parsing, JSON parsing, and any programming language parsing. The output tree is called Parse Tree or Abstract Syntax Tree. In HTML context, it is called Document Object Model (DOM).

A CSV file parsing can result in a List of values or a List of Record objects.

Graph Type is a choice for natural language parsing.

A piece of program that does parsing is called Parser.

What does a parser do?  

A well-made parser will distinguish which information of the string is needed, and in accordance to the parsers, pre-written code, and rules, it will pick out the necessary information and convert it into JSON, CSV, or a table, for example.

It’s important to mention that a parser itself is not tied to a data format. It’s a tool that converts one data format into another, how it converts it and what depends on how the parser was built.

Why do we need parsing?

We need parsing because different entities need data to be available in various forms. Parsing allows transforming data in a way that can be understood by specific software. The obvious example is programs — humans write them, but computers must execute them. So, humans write them in a form that they can understand; then, software transforms them in a way that a computer can use.

Where is parsing used?

Parsers are used for many technologies, including:

  • Cognitive Search
  • Java and other programming languages
  • HTML and XML
  • Interactive data language and object definition language
  • SQL and other database languages
  • Modeling languages
  • Scripting languages
  • HTTP and other internet protocols

How does parsing work?

Parser analyses source text against the format prescribed. If source text does not match against format error is thrown or returned.

If source text does not match against format, an error is thrown or returned.

If matches, then “data structure” is returned.

Parsing in Engati

Parsing plays a vital role in Engati, especially when it comes to Smart Responses. A Smart Response is a tool that streamlines the current chatbot setup experience to make it easier for you to set up a chatbot as quickly and effectively as possible. 

There are currently 4 ways to set up a smart response. The one we’ll be focusing on is DocuSense.  DocuSense aims to provide you the ability to upload documents used to answer chatbot users’ queries. It also minimizes the bot training effort and offers the option to combine answers to user queries from multiple FAQs and cognitive search sources. This widens the capability of the bot to provide more appropriate responses, reduces effort and time consumed, leading to a more intelligent bot with lesser efforts.

How it works

Customers ask complex questions, like finding a specific policy or questions about a particular guideline, which can’t be answered with simple FAQ matching. Adding FAQs for these particular questions may get cumbersome, so instead, we’ve given you the option to directly upload all of your policies to our NLP Engine. 

The more information you feed the engine, the better it becomes. As customers ask questions, the NLP Engine parses through your document and matches the string to provide an answer. 

 

About Engati

Engati powers 45,000+ chatbot & live chat solutions in 50+ languages across the world.

We aim to empower you to create the best customer experiences you could imagine. 

So, are you ready to create unbelievably smooth experiences?

Check us out!

Parsing

October 14, 2020

Table of contents

Key takeawaysCollaboration platforms are essential to the new way of workingEmployees prefer engati over emailEmployees play a growing part in software purchasing decisionsThe future of work is collaborativeMethodology

What is parsing?

Parsing is the process of analyzing a string of symbols, either in natural language, computer languages, or data structures, conforming to formal grammar rules.

Data parsing

Data parsing is a method where one string of data gets converted into a different type of data. So let’s say you receive your data in raw HTML. A parser will take the said HTML and transform it into a more readable data format easily read and understood.

The 3 types of parsing

Tree type is a common and standard choice for XML parsing, HTML parsing, JSON parsing, and any programming language parsing. The output tree is called Parse Tree or Abstract Syntax Tree. In HTML context, it is called Document Object Model (DOM).

A CSV file parsing can result in a List of values or a List of Record objects.

Graph Type is a choice for natural language parsing.

A piece of program that does parsing is called Parser.

What does a parser do?  

A well-made parser will distinguish which information of the string is needed, and in accordance to the parsers, pre-written code, and rules, it will pick out the necessary information and convert it into JSON, CSV, or a table, for example.

It’s important to mention that a parser itself is not tied to a data format. It’s a tool that converts one data format into another, how it converts it and what depends on how the parser was built.

Why do we need parsing?

We need parsing because different entities need data to be available in various forms. Parsing allows transforming data in a way that can be understood by specific software. The obvious example is programs — humans write them, but computers must execute them. So, humans write them in a form that they can understand; then, software transforms them in a way that a computer can use.

Where is parsing used?

Parsers are used for many technologies, including:

  • Cognitive Search
  • Java and other programming languages
  • HTML and XML
  • Interactive data language and object definition language
  • SQL and other database languages
  • Modeling languages
  • Scripting languages
  • HTTP and other internet protocols

How does parsing work?

Parser analyses source text against the format prescribed. If source text does not match against format error is thrown or returned.

If source text does not match against format, an error is thrown or returned.

If matches, then “data structure” is returned.

Parsing in Engati

Parsing plays a vital role in Engati, especially when it comes to Smart Responses. A Smart Response is a tool that streamlines the current chatbot setup experience to make it easier for you to set up a chatbot as quickly and effectively as possible. 

There are currently 4 ways to set up a smart response. The one we’ll be focusing on is DocuSense.  DocuSense aims to provide you the ability to upload documents used to answer chatbot users’ queries. It also minimizes the bot training effort and offers the option to combine answers to user queries from multiple FAQs and cognitive search sources. This widens the capability of the bot to provide more appropriate responses, reduces effort and time consumed, leading to a more intelligent bot with lesser efforts.

How it works

Customers ask complex questions, like finding a specific policy or questions about a particular guideline, which can’t be answered with simple FAQ matching. Adding FAQs for these particular questions may get cumbersome, so instead, we’ve given you the option to directly upload all of your policies to our NLP Engine. 

The more information you feed the engine, the better it becomes. As customers ask questions, the NLP Engine parses through your document and matches the string to provide an answer. 

 

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