Natural Language Processing
We all know that ChatGPT has taken the world by storm. True, it is a major advance of Artificial Intelligence in the area of Natural Language Processing. Many may not know that WolframAlpha, launched in 2009, allowed natural language queries. As a long time user of Wolfram Mathematica, I was pleasantly surprised when the product […]
In a series of articles written earlier, I had shown how it is possible to model Definite Clause Grammars (DCG) in LispWorks Lisp (Enterprise Edition). We use defgrammar in Common Prolog (available as part of KnowledgeWorks package) to define our grammar rules. Here is a toy English grammar represented using defgrammar: This corresponds to the following Prolog […]
In the last article, I talked about determining sentence types automatically. Another interesting task is to generate the “negation” of a given sentence. Example-1: Sentence => “My teacher lives nearby” Negation => “My teacher does not live nearby” Example-2: Sentence => “She did not like that speech” Negation => “She liked that speech” I have […]
Sentences in English can be classified into the following common types: – Simple sentence (“I am drinking coffee”) – Compound sentence (“He came home with his school friend and they had an enjoyable evening”) – Complex sentence (“Whenever my dog barks, I give him some biscuit”) – Imperative sentence (“Please keep quiet”) – Interrogative sentence […]
WH-Questions are questions that begin with the following words: – Who (“Who came here yesterday?”) – What (“What is the goal of this project?”) – When (“When can I visit my parents?”) – Where (“Where did he go?”) – Why (“Why is everyone running away?”) – Which (“Which is the book you recommend?”) – How […]
iLexicon is an “intelligent” dictionary that can be used to build Natural Language applications. I have two implementations, one in Lisp and another in Prolog. Both implementations are memory-based, in order to speed up performance. I have written several articles referencing it, for example see this. LiteDB is a NoSQL database for .NET. I […]
In my previous article, I showed how “iLangGen” framework facilitates text generation using templates. I talked about the various “patterns” that can be used in a template. However, in that article, I did not go into the details of the “Embedded Template” pattern. That is the focus of today’s article. Embedded Template This pattern allows […]
I had written earlier about natural language generation using my iLangGen framework. I used a “template” text file which was instantiated dynamically based on predefined “grammars” and external data. The sample application I show-cased demonstrated its utility and versatility. Today I would like to touch upon a few other “pattern” elements that can be embedded in […]
Extracting meaningful information from unstructured, human readable text is a hot topic of research today and has important applications in many domains. I have written a few blogs related to this topic, for example, see this and this. In today’s article, I would like to show how Mathematica can be a great help when working with […]
The iLexicon system can handle active/passive voice conversion of fairly complex English sentences. I gave examples of the underlying verb conjugation mechanism in this article and this one. Today, I am going to give examples of the conversion of complete sentences. Here is an example of active to passive voice conversion: The above is a snapshot […]
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