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What is Natural Language Generation (NLG) & where is it used?

Reading Time 14 mins | May 5, 2021 | Written by: AX Semantics

What is Natural Language Generation (NLG) & where is it used?

The acronym NLG stands for Natural Language Generation. Natural Language Generation is a subfield of artificial intelligence (AI). AI-powered content creation uses artificial intelligence technology to create content.

Just a few years ago, this technology was considered unrealistic and unattainable. However, today we are witnessing a massive shift in content marketing and most companies have already adopted this technology.

Artificial intelligence is an excellent tool for automated content creation as it can process large amounts of data in seconds without the need for editors to write content. A human can write a thousand words per hour, while AX Semantics' automated content creation software can write the same amount in seconds.

NLG programs produces natural language output with the help of ai, analyzing structured data and translating it into text. If you have a lot of data-driven information that needs to be articulated, you can feed it into Natural Language Generation software like AX Semantics'.

What to expect in this article:

What is the use of Natural Language Generation?

Many texts are based on complex sets of data. Hiring humans to turn data into texts is both time-consuming and expensive. NLG software for Automated Content Creation can do the job faster and cheaper, provided that the structure of the data and the required texts are essentially identical. The benefits of NLG are therefore primarily economic.

How does Automated Content Generation using NLG differ from outsourced copywriting?

A copywriter typically helps organize information and structure a coherent story. The copywriter uses words and phrases that connect with the target audience, convey credibility, and encourage buying behavior. When a large company hires a copywriter, it takes months to create thousands of unique product descriptions. However, with an NLG-based tool like AX Semantics, this process can be completed in a few hours.

The automated content creation software uses automation tools and techniques to increase efficiency and allow employees to focus on other essential tasks.

So, the main difference between the two is that copywriters spend much more time writing descriptions, while automated content creation is a continuous and scalable process. Once a project is configured, the software repeatedly creates product descriptions with just one click and without any additional effort.

How does Natural Language Generation (NLG) work?

You train a Natural Language Generation software to extract relevant information from a set of structured data and include the information in a sentence or paragraph.

AX Semantics’ very own software for Automated Content Creation works with JSON-files. The can contain all kinds of information. In so-called “projects” you can configure the software to focus on certain information and to ignore or exclude irrelevant data. The commands you write are similar to what writing a program would look like:


The next step is to, write a generic text and link single sentences or whole paragraphs to the commands you have written. This way, the variable information is included in the text.

What you end up with are texts that are similar in structure but different in content. Depending on your preferences and how you use the AX Semantics software, each sentence may sound the same or completely unique. Either way, the software is programmed to make sure that you never get two identical texts to avoid creating duplicate content.

AX Semantics NLG software supports 110 languages, so you can easily implement a multilingual project. All you have to do is translate the content parts. Logics and rules can be taken from the source language.

You want to know how automated content generation with AX Semantics works?

Watch the short video about the functionality and benefits of the software:

How to automate content writing with AX Semantics explained in less than 2 minutes

What are the benefits of Natural Language Generation?

If used correctly, NLG has many benefits. Not only can you save time writing data-driven content. You can also scale your content creation.

Once set up, you only need to update your data and make a few clicks to generate thousands of new and unique texts. The texts are updated whenever the data changes, ensuring that sure your content always contains the most up-to-date information.

So, what the AX Semantics Natural Language Generation software can promise you, is:

  • Time Savings
  • Human Resource Savings
  • Scalable Automated Content Creation
  • Up-to-date content

What is the difference between NLG and NLU (Natural Language Understanding)?

Natural Language Generation (NLG) is often thought of as the opposite of the equally-popular Natural Language Understanding (NLU), a form of computer process that breaks down the existing language is broken down into structured and easy-to-understand data.

NLG performs the opposite function, converting data into a readable, grammatically accurate copy that can be used online, in reports, and in many other places.

NLG and NLU combined result in Natural Language Processing (NLP).

Content created using NLG can be:

  • highly tailored and targeted to a particular audience
  • transform information or data into a more understandable form

How is Natural Language Generation used?

Natural Language Generation is an increasingly popular tool used by businesses and companies of all shapes and sizes. It provides an effective and practical way to translate large volumes of data into a meaningful copy that is easier to understand, more functional to use, and more deliberate in targeting its audience. You need a Natural Language Generation software if you write or need

  • similar texts with variable details
  • texts based on data or statistics

Some main uses for NLG include:

1. Automate readable financial or medical reports from data

One of NLG's key design features is its ability to turn raw data into easy-to-understand reports and documents, especially when dealing with large amounts of data or information that requires precise translation. NLG takes this information and, using the AI with which it is equipped, creates content that reflects the results and analysis of this data.

This functionality makes NLG ideal for:

  • financial sectors
  • scientific areas
  • business areas

In these areas,accurate and credible reporting is a must. This also applies to the use of NLG for status reporting and maintenance in both closed databases and broader systems.

2. Generate high-volume content for web applications and mobile tools

Alongside more traditional data-driven content, NLG can also be used to produce large volumes of relevant, grammatically-accurate content for use in the population of websites, mobile applications and more.

While this content may still need modification and additional creative design, especially with more emotive language and localization, NLG can be used as a tool to reduce the time and energy spent on creating volumes of content that would otherwise be costly if written by a human.

By understanding the target audience and the ability to mimic speech and tone styles, NLG tools can create highly effective and high-quality content quickly and easily

3. Create personalized customer communication

While it may seem like the least obvious use of Natural Language Generation, this unique functionality is one of the key benefits of using AI within a business that provides active customer service.

A well-designed and targeted NLG system provides efficient customer communications and support, commonly seen as an AI chat function on many brands’ websites and platforms. NGL is perfectly designed for this functionality, thanks to its ability to be flexible depending on the customer's specific requirements.

Where is NLG used?

Natural Language Generation (NLG) is used around the world by people who need to create large amounts of content quickly, conveniently, and accurately. As the modern version of a ‘text robot, NLG is far more reliable, functional, and practical than previous iterations of AI, making it a valuable addition to the toolkit of countless businesses and industries.

Content creation can be a burden for many services that don’t have the budget to hire copywriters or content creators for high volumes of text creation. However, NLG provides a solution to create that content quickly and easily without additional costs.

Beyond the convenience and effectiveness of Natural Language Generation, content automation is also a valuable and practical way to quickly access to reports quickly, in a format that’s designed to be readable and understandable. The ability to effectively target an audience and create content based on these specific requirements and the data provided makes NLG uniquely suited for business reporting and key data analysis in sectors such as scientific studies, the financial industry, and business development and analysis.

What types of NLG Software are there?

There are two NLG technologies: GPT and Data-to-Text. But how do they differ?

Data-to-Text software allows you to generate high-quality text based on structured data. This means that you, as a user, are always in control over the text results. You can intervene in the text creation process at any time and make adjustments. This control ensures the consistency of the text quality as well as the topicality and correctness of the texts. The Data-to-Text software is particularly suitable if you want to create hundreds or thousands of different high-quality product descriptions within a few moments. This saves you time and money, and makes it easier to maintain and customize your content. You'll also achieve more conversions and generate more traffic to product detail pages.


GPT stands for "Generative Pre-trained Transformer". This is a large language model that has been trained with hundreds of billions of texts from the Internet. In contrast to Data-to-Text, the GPT model is particularly suitable for generating individual texts. The user has no control over the generated content, and proofreading is essential because the quality of the texts varies greatly.
The following overview shows you a brief summary of which technology has which functions and for which use cases they are suitable. The overview is available as a free download:

Natural Language Generation for small companies & large corporations

Our clients are often mid-sized to large companies. Especially online marketers with large online stores turn to our Natural Language Generation software to automate product descriptions or content for category pages.

However, it is also popular with those who work with a lot of data, like analysts who work with risk and compliance reports or finance sheets. It also appeals to companies in the medical, pharmaceutical, finance and banking, and engineering industries. Our list of clients speaks for itself and gives an insight into the types of businesses that rely on our Automated Content Creation software.

Is Natural Language Generation right for me?

If you think that Natural Language Generation is the ideal content automation choice for your requirements, you’re not alone. Join the countless businesses that are integrating AI into their day-to-day processes. Contact us today to learn more, or take a look at our existing content and articles to learn a little more about what Natural Language Generation can do for you.

Background Information About Content Automation with AX Semantics

What is automated content?

Automated content uses artificial intelligence and automated processes to create different types of content. Users only need to configure rules and logic and use them to decide how data should appear in the texts. The rules are configured only once at the beginning. Then, the tool applies the rules to thousands of texts that are generated.
Depending on which AI tool you choose, you can automatically generate entire articles or shorter texts, such as product descriptions and content for social networks.

How to use AX Semantics?

To use our software effectively, you only need to follow three steps:
1. Upload their data to the platform either in CSV format or other popular file formats. 
2. After the integration is complete, you need to configure the rules. Set the tone and approach to your content. 
3. Lastly, you just need to wait for the AI-driven technology to create the content based on your ingested data and set rules. You can update and refresh all your content as often as you want!

What are the most common use cases of content automation?

Content automation seeks to automate as many subtasks as possible to avoid repetitive manual processes and increase efficiency. This is done by using AI-powered NLG (natural language generation) and NLP (natural language processing) technology for various types of content creation. As a result, you get relevant content that is optimized and ready to drive some conversions. The most common use cases of content automation include:
- Creating business reports and critical data analysis in areas such as scientific studies, finance, and business development and analysis
- Creation of product descriptions or content for category pages
- Creation of risk and compliance reports or financial reports
- Creation of medical, pharmaceutical, financial, and banking or technology reports

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