Artificial intelligence is one technological marvel that’s revolutionizing nearly all business sectors. There are myriad branches and techniques within AI, and one of the prominent among them is Natural Language Processing (NLP).
Natural Language Processing and its sub-type, Natural Language Generation, help computer systems process, understand, and generate natural human language. Any time you use any online essay typer or rewriter, it is NLG/NLP working behind the scenes.
So, what is natural language generation? And how can NLG systems generate or rewrite an entire essay like human beings?
Natural Language Generation in Natural Language Processing
From online essay rewriting tools to chatbots, machine translation, freeform answer generation, natural language generation (NLG) models find usage in any setting where computerized systems need to generate new text automatically.
So, what is Natural Language Generation?
Natural Language Generation is a subset of Natural Language Processing (NLP). It is one of the most important problems in NLP, which in turn is a subfield of AI that is again a part of cognitive computing science.
As human writers, we think of many different things to develop proper, understandable content. Logic, flow & cohesion, grammar & structure, diction & correctness – so many different parameters and requirements must be addressed. Designing an NLG system requires addressing all those parameters, aspects, and sub-tasks.
Natural Language Generation purviews the design of AI systems with a wide variety of applications in text generation from any data, visual, encoded, or other data formats. NLG research and development generally focuses on three primary scenarios, namely:
. Data-to-Text Generation, where the text is generated from some structured or unstructured data;
. Text-to-Text Generation, which generally involves fusing information from multiple textual sources;
. Dialogue Generation, where texts in context with an ongoing conversation need to be generated
When it comes to essay typers or rewriters, the primary focus or scenario of the underlying natural language generation system is data-to-text generation. Despite being complicated and quite hard to understand at one go, their performance across all NLG scenarios has been immensely successful.
The AI Mechanisms Used
Generative language models produce spontaneous output in the natural language, which is substantially complicated. There are multiple stages involved, many of which an educated human like you and me take for granted. Goes without saying that the techniques employed need to be advanced and intricate. That’s why deep learning and neural networks come into the picture!
Deep learning-powered artificial neural network systems are incredibly advanced AI technologies that work together to carry out and synchronize all the different stages of natural language generation.
Interested in finding out what those stages are? The following section looks at the different stages of AI essay writing/rewriting and a brief look at the core neural network technology powering AI writing tools.
NLG-Powered Essay Rewriters: A Look Under The Hood
Ever introspected your thinking process when trying to communicate in any language? How do you use words and grammatical rules to frame sentences and thread them together to convey some message?
The human brain imbibes all the stages and processes involved in comprehending natural language and using it to convey information. And all these decisions and processes must be addressed in natural language generation using AI.
There’s room for debate regarding the appropriate sub-tasks involved in language generation. However, the NLG community agrees upon six basic processes for mapping natural language input to a final output text.
Any AI-powered essay rewriter on any reputed essay homework help service executes the following stages while developing content.
Here’s a quick overview of every one of them à
- Content Determination
This is the first stage where a decision regarding the information presented in the content is taken. NLG-powered essay rewriters create a set of data objects used for subsequent steps. The data contained within these objects differ as per the nature of the input information and the context. Data objects thus created are labelled as per the relation between the information contained within the input data.
Discourse Planning
This stage involves imposing order and structure over information or messages to be conveyed. Discourse planning processes make decisions regarding how information is to be presented and the underlying structure.
The output of a discourse planner is a tree-like structure whose nodes represent pieces of information while the branches reflect the relationships between the entities. The relationships and the node groupings dictate the sentence structure, the structure of paragraphs, and the overall content.
The content determination and discourse planning stages concern themselves with the pragmatics and semantics of the content.
- Sentence Aggregation
The outputs from the discourse planner comprise a tree structure with messages grouped as per specifications and the nature of the message. The sentence aggregation stage accumulates the different messages grouped and forms sentences as per their relationships.
The aggregation stage is optional, as different sentences can convey messages. Acute sentence aggregation can however enhance the fluency of any natural language content.
Lexicalization
The lexicalization stage determines the morphological structure of the content to be generated. Decisions regarding the most appropriate words and phrases to express the domain concepts and relations in the message.,
For example, suppose the NLG essay rewriter intends to describe some process. In that case, the lexicalization stage determines whether and how often to use words such as elaborate, elucidate, phenomenon, activity, and the like.
- Referring Expression Generation
Here, in this stage, the NLG system chooses the words or phrases that refer to the domain entities in a message. So, if the essay rewriter is modifying an essay on trains, the term train/s and the name of a particular train can be the referring expression.
The referring expression generator stage works in tandem with the lexicalization stage as they both work together to determine the surface linguistic objects. However, referring expression generation is much more discriminatory and needs substantial information to distinguish a referring expression from all the different domain entities. Referring expression generators consider contextual information or the discourse history to find the right referral expression in a particular context.
The Layers of Linguistics
- Linguistics Realization
Linguistic realization is the final stage and applies the language-specific grammatical rules to develop a text (essay, blog, review, critical analysis, answers to questions, responses to queries, etc.), which are syntactically, morphologically, and orthographically accurate.
Morphology and orthography are closely associated with a particular language’s syntactical or grammatical rules.
All the above stages/sub-tasks are distributed among specific essay writer/rewriter architecture modules. We wrap up this write-up with a look at the generic architecture of any NLG system, be it an essay typer or rewriter.
The Architecture of an NLG System
The different decision-making processes involved in text generation must be divided into tasks and modules. Online AI rewriters in a custom essay writing help service comprise the following modules:
.The Document or Text Planner,
.The Microplanner or Sentence Planner
.The Surface Realiser.
(Do note that this is not the only way to design or architect an NLG-powered essay rewriter.)
Each of the above modules is responsible for executing a specific stage of the natural language generation process.
- 1. The document or text planner is concerned with content determination and discourse planning.
- 2. The micro planner/sentence planner supervises the sentence aggregation, lexicalization, and referring expression generation stages.
- 3. The surface realizer takes care of all linguistic realization sub-tasks, such as using the right words & phrases, applying the right grammatical rules, spelling, capitalization, punctuations & the like, to craft or rewrite flawless content.
Well, that’s about it for this write-up. Hope it was an informative & exciting read for one & all.
If NLG has garnered your interest, then know that it is heavily technical, combining computational linguistics, applied mathematics, deep learning, software engineering, and computer science. Work hard and use essay rewriters only from reliable essay homework help services.
All the best!
Author-Bio: Timothy Barton is a computer science professor from a major public research university in Toronto, Canada & also a great assignment writer He is the brains behind the AI- essay typer and essay rewriter on MyAssignmenthelp.com, a leading assignment and essay homework help service.
