Malayalam Named Entity Recognition using morphology analyser

Named Entity Recognition, a task of identifying and classifying real world objects such as persons, places, organizations from a given text is a well known NLP problem. For Malayalam, there were several research papers published on this topic, but none are functional or reproducible research. The morphological characteristics of Malayalam has been always a challenge to solve this problem. When the named entities appear in an inflected or agglutinated complex word, the first step is to analyse such words and arrive at the root words. [Read More]

Malayalam morphology analyser – First release

I am happy to announce the first version of Malayalam morphology analyser. After two years of development, I tagged version 1.0.0 . In this release In this release, mlmorph can analyse and generate malayalam words using the morpho-phonotactical rules defined and based on a lexicon. We have a test corpora of Fifty thousand words and 82% of the words in it are recognized by the analyser. A python interface is released to make the usage of library very easy for developers. [Read More]

Malayalam morphology analyser – status update

For the last several months, I am actively working on the Malayalam morphology analyser project. In case you are not familiar with the project, my introduction blog post is a good start. I was always skeptical about the approach and the whole project as such looked very ambitious. But, now I am almost confident that the approach is viable. I am making good progress in the project, so this is some updates on that. [Read More]

The many forms of ചിരി ☺️

This is an attempt to list down all forms of Malayalam word ചിരി(meaning: ☺️, smile, laugh). For those who are unfamiliar with Malayalam, the language is a highly inflectional Dravidian language. I am actively working on a morphology analyser(mlmorph) for the language as outlined in one of my previous blogpost. I prepared this list as a test case for mlmorph project to evaluate the grammar rule coverage. So I thought of listing it here as well with brief comments. [Read More]

Number spellout and generation in Malayalam using Morphology analyser

Writing a number 6493 as six thousand four hundred and ninety three is known as spellout of that number. The most familiar example of this is in cheques. Text to speech systems also need to convert numbers to words. [][1]Source: https://commons.wikimedia.org/wiki/File:Sample_cheque.jpeg by User:Tshrinivasan The reverse process of this, to convert a phrase like six thousand four hundred and ninety three to number 6493 – the number generation, is also common. [Read More]

Towards a Malayalam morphology analyser

Malayalam is a highly inflectional and agglutinative language. This has posed a challenge for all kind of language processing. Algorithmic interpretation of Malayalam’s words and their formation rules continues to be an untackled problem. My own attempts to study and try out some of these characteristics was big failure in the past. Back in 2007, when I tried to develop a spellchecker for Malayalam, the infinite number of words this language can have by combining multiple words together and those words inflected was a big challenge. [Read More]