Natural Language Processing
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 […]
In my earlier article, I showed how the iLexicon system can generate verb conjugations based on <Verb, Tense, Person, Number> quadruple. For the 16 tense forms discussed in that article, the verb conjugations were generated in “active” voice. We all know that “transitive” verbs can be expressed in both “active” and “passive” voice. For example, […]
After my last book review, I decided to check out a few websites that claim to simplify English text and/or help compute the measure of readability. In today’s post, I am sharing the results of my experiment. www.simplish.org This site has some interesting functionality. It does spelling check, grammar check, text simplification, and can even […]
Title: Automatic Text Simplification Author: Horacio Saggino Publisher: Morgan & Claypool Publishers Year: 2017 Automatic Text Simplification is an active area of research in NLP and has been going on for over 20 years. The idea is to transform a given text T1 into text T2 such that T2 is easier to read and understand […]
In the previous article, I showed how we can use ATNs for extracting key information from natural language text. I also pointed out in that article that Definite Clause Grammars (DCG) are a more compact formalism for doing this. That will be the focus of today’s article. For a nice introduction to DCG, read this. […]
After Wood’s paper [1], Augmented Transition Networks (ATN) became popular in the 1970s, for parsing text. An ATN is a generalized transition network with two major enhancements: Support for recursive transitions, including jumping to other ATNs Performing arbitrary actions when edges are traversed Remembering state through the use of registers See the “Further Reading” section at […]
In the last article, I showed how to generate verb conjugations in the “iLexicon” system. Today, let us see how this idea can be extended to English “phrasal verbs”. According to Wikipedia: “a phrasal verb is a phrase such as turn down or ran into which combines two or three words from different grammatical categories: […]
We have been taught in school that English language has different “tense” forms. To help you quickly recollect, I am listing them in the table below (the verb ‘sleep’ is used as example): No. Tense Form Example Sentence (3rd Person Singular Pronoun) 1 Simple Present She sleeps 2 Simple Past She slept 3 Simple Future […]
Working with word patterns can be an exciting (and challenging) creative activity. Such patterns come into picture while playing word games, solving word puzzles or even writing poetry. It is precisely to facilitate such tasks that I am building my “iLexicon” system. One popular word game goes like this: The first player utters a word, […]
Recent Comments