LISP
In the previous post, we saw how to invoke a Go function from Lisp. In today’s post, I would like to explain how to go in the other direction, namely, how to call Lisp functins from Go. There are two ways to do this. The first approach is to load the Lisp DLL (like any […]
For the past few weeks I was travelling in the USA and had the pleasure of meeting several friends, some of whom are senior developers and architects. It was interesting to learn that many of them were either using Go language in their daily work, or were passionately endorsing the language! Due to lack of […]
A few weeks ago I had written about my brief experiment with Mathematica’s new feature, which provides answers to questions based on given text. After that post, I spent some time thinking about how to implement something similar. In today’s post, I want to show you what I have been able to do in the […]
I had written a series of posts on my iLangGen framework last year. It aims to provide a flexible and expressive approach for building natural language generation systems. In today’s post, I would like to describe a concrete example of how iLangGen can be used for generating natural language text from structured data, aided by […]
According to Wikipedia, “A kangaroo word is a word that contains letters of another word, in order, with the same meaning. For example: the word ‘masculine’ contains the word ‘male’, which is a synonym of the first word; similarly, the word ‘observe’ contains its synonym ‘see’.” Interesting idea. The key point to note is that […]
Detecting sentiments and emotions in a piece of text are frequently performed activities in Text analysis. There are some API services available for this. For example, meaningcloud.com has an API for detecting sentiments in the text submitted to it. Another API service provider is aylien.com . Emotion detection for text is supported by qemotion.com. Because […]
I had earlier briefly talked about the Ilexicon project that I have been working on for some time now. The goal is to build an intelligent dictionary that will come in handy while implementing NLP applications such as recognizers and generators. In today’s post, I want to demonstrate some cool features available in iLexicon. At present iLexicon […]
If you are into writing poems, stories or essays, or you just have a fascination for words, I encourage you to take a look at Datamuse. Recently I was studying about the structure of various poetic forms, and in the process of browing different sites, I stumbled upon Datamuse. I found it to be pretty […]
One of the advanced features of iLangGen is the ability to embed arbitrary function calls on the RHS of grammar rules. Such functions impart interesting dynamic behaviour to the generated data. For convenience and flexibility, iLangGen supports two types of function calls – Direct and Indirect. In the case of the Direct function call, the […]
In the last post, we saw how iLangGen text generation framework supports reuse of grammars through inheritance, akin to object-oriented languages. The good news is that we can achieve reuse through composition as well. The following is a simple grammar, nothing fancy to elaborate. Here is the output when you traverse the grammar without AST. […]
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