Natural language processing (NLP) is a wonderful technology. It is a derivative of artificial intelligence. In simplest terms, it is a technology that enables computers to understand and manipulate natural languages.
This means computers are now better at interfacing with human beings because they can converse or interact with them using natural language.
This has endless possibilities. One of which is the use of NLP in programs that can help aspiring writers. Online rewording tools are one such example. They are powered by AI, which is just a fancy way of saying they use NLP.
Today we are going to look at how such tools work and how they reword text to generate new words using examples.
NLP Process in Rewording Tool
1. Text Analysis
NLP has a whole process. This process has multiple steps. When they are done, the tool is capable of understanding and manipulating text.
The first step in this process is the analysis of the text. This is also known as syntax analysis. The following things happen in syntax analysis.
- Tokenization
- Recognition of words using stop characters
- Recognition of sentences
- Recognition of stop words
Tokenization is the process of breaking down a text into its most basic parts. Usually, that means that everything is broken down into their characters. But how do computers know which string of characters is a word or not?
That’s where stop characters are used. Stop characters include periods, commas, blank spaces, question marks, and exclamation marks. These tell the system that a word string has ended.
This information is used to recognize sentences as well. Finally, we have recognition of stop words. Stop words as opposed to stop characters are just useless words that add nothing to the semantics.
During text analysis, such words are removed from the text to create an accurate semantic representation.
2. Semantic Analysis
Semantic analysis is the part of NLP where the computer tries to understand the meaning of the text. This is the part that is the most important because it enables computers to understand the context.
It allows them to look beyond the literal meaning of the word by analyzing its surrounding parts.
Some techniques used in this stage are:
- Word sense disambiguation. In this technique, the context is found by checking the sentences coming before and after the subject.
- Semantic role labeling. In this technique, the words in a sentence are labeled by understanding whether they are verbs, objects, subjects, adjectives, etc., etc.
- Ontologies and knowledge bases. Sometimes, the NLP system uses structured representations of concepts to understand the text. Other times they use databases of words and their possible meanings.
These are just some ways in which semantics are understood by NLP systems. Once the semantics are understood, an NLP reworder can start doing its thing. The semantic representation created during the semantic analysis helps in rewording efficiently.
3. Rewording Techniques
There are multiple rewording techniques that an NLP reworder can use. They are listed and discussed below.
a. Synonym Replacement
The most basic technique of rewording is to replace select words from the text with their synonyms. This is known as synonym replacement. Now we will show you some examples of a reword generator that can do synonyms replacement.
As you can see the words are replaced with synonyms. The sentence looks different and makes sense, but its readability is reduced. That’s why this technique is most often used in conjunction with others rather than on its own.
a. Phrase Change
Phrase change is the same as synonym replacement except this time only phrases are changed rather than words. The phrases may be replaced with either words or other phrases. Here is an example of a reword generator doing a phrase change.
As you can see a few different phrases have been changed by the reword generator. They are emboldened and contextually accurate as well.
a. Structure Alteration
Another technique used by reword generators is changing the sentence structure. This is an advanced technique, but due to NLP, it is possible. Given below is an example of a reworder changing the sentence structure of some given text.
It is very subtle, but rest assured it has happened. And you probably noticed that other techniques have also been used to make the rewording more thorough.
1. Error Checking and Selection
The final part of NLP paraphrasing is to check the reworded content for errors and mistakes. This involves checking if the meaning has remained unchanged, whether the context was preserved, or whether the changes made were grammatically correct or not.
This is a necessary step because the data gained from it is used to improve machine-learning models. The more data they get the better they become. So, error checking results in better AI reworders.
Many AI rewording tools generate different versions of the text in one go. But they don’t use all of them at once. Instead, they evaluate and compare each other. The idea is to select the best version of the text. And only that final version is shown to the users.
In all the examples that we showed you earlier, this is happening as well. Since this process happens at the back end, we cannot see it for ourselves.
Conclusion
So, there you have it, the NLP process and examples of rewording using that process. We showed you real-life examples by using real tools. Now you should have a rudimentary understanding of how NLP works and how the best rewording tools use it to create natural-sounding text.
👤 About the Author
Ashwani is passionate about DevOps, DevSecOps, SRE, MLOps, and AiOps, with a strong drive to simplify and scale modern IT operations. Through continuous learning and sharing, Ashwani helps organizations and engineers adopt best practices for automation, security, reliability, and AI-driven operations.
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