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 impress with their intelligence, 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'.

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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. An NLG software for Automated Content Creation can take over this task faster and cheaper – if the structure of the data and the required texts, in essence, is always identical. The benefit of NLG, therefore, is mainly an economic one.

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 matter of 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 pull out relevant information from a set of structured data and include the information in a sentence or paragraph.

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

If FIELD A contains INFORMATION B, do TASK C.

In a next step, you write a generic text and link single sentences or whole paragraphs with the orders you wrote. This way, the variable information is included in the text.

What you end up with are texts that are similar in structure but different when it comes to the content. Depending on your preference and how you use our software, each sentence may sound the same or completely unique. Either way, the software is programmed to make sure you get no two texts that are identical as 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.

What are the benefits of Natural Language Generation?

If used correctly, NLG has a lot of benefits. Not only can you save time to write 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, making sure your content always contains the most recent information.

So, what Natural Language Generation software can promise you, is

  • Time Savings
  • Human Resource Savings
  • Scalable Automated Content Creation
  • Up-to-date content
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What is the difference between NLG and NLU (Natural Language Understanding)?

Natural Language Generation is often seen as the opposite of the also-popular Natural Language Understanding, a form of computer process where the existing language is broken down into structured and easy-to-understand data. NLG provides the opposite function, taking data and transforming it into a readable, grammatically accurate copy that can be used online, in reports, and in many other places. Both together 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 reporting and credible reports are a must. This also applies for the used of NLG for reporting statuses and maintenance within 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 high volumes of relevant, grammatically-accurate content for use in the population of websites, mobile applications and more.

While this content may still need amendment 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 high-cost if completed directly 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 hyper-personalized customer communications
While it may seem like the least apparent 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 can offer 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 is around the world, and individuals in need of the fast, convenient, and accurate creation of large volumes of content. As the modern version of a ‘text robot’, NLG is far more reliable, functional and practical than past AI iterations, making it a valuable addition to the toolkit across countless businesses and industries. Content creation can strain on many services where there isn’t a budget to hire copywriters or content creators for high volumes of text creation. Still, NLG provides a solution to create that content quickly and easily without the need for additional costs.

Beyond the convenience and effectiveness of Natural Language Generation, content automation is also a valuable and practical way to gain access to reporting 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 creating of business reports and essential data analysis in sectors such as scientific studies, financial industries, and business development and analysis.

Natural Language Generation for small companies & large corporations

Our clients are often middle-class companies to big enterprises. Especially online marketeers with extensive online shops are turning towards 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 is also interesting for companies in Medical, Pharma, Finance, and Banking, or Engineering industries. Our list of clients speaks for itself and gives an impression on what business fields rely on our Automated Content Creation software.

Is Natural Language Generation for me?

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

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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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