Towards Building a Computational Sense Inventory from the Monier-Williams Dictionary Using Clustering Techniques

2026-06-08 · Source: Paper Index on ACL Anthology · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Data Science & Analytics, Computational Linguistics · Depth: Expert, quick

Summary

A research paper titled "Towards Building a Computational Sense Inventory from the Monier-Williams Dictionary Using Clustering Techniques" by Anagha Pradeep, Sriram Krishnan, and Radhika Mamidi, presented at the 8th International Sanskrit Computational Linguistics Symposium in March 2026, details efforts to construct a computational sense inventory. This initiative focuses on extracting and organizing word senses from the extensive Monier-Williams Dictionary, a foundational resource for Sanskrit studies. The authors propose utilizing clustering techniques to automate the process of identifying and grouping distinct meanings of words, thereby creating a structured digital resource. Published by the Association for Computational Linguistics, this work, spanning pages 32–46, aims to enhance computational linguistic tools for Sanskrit by providing a robust, machine-readable inventory of word senses, crucial for tasks like word sense disambiguation and semantic analysis in natural language processing.

Key takeaway

For NLP engineers or research scientists focused on developing semantic resources for Sanskrit or other low-resource languages, this work highlights a viable approach. You should consider applying clustering techniques to existing digital dictionaries, like the Monier-Williams, to automatically construct computational sense inventories. This method can significantly reduce manual effort in lexicographical data preparation, accelerating the development of tools for word sense disambiguation and other advanced NLP tasks in these languages.

Key insights

Computational sense inventories for Sanskrit can be built from the Monier-Williams Dictionary using clustering techniques.

Method

Clustering techniques are applied to definitions within the Monier-Williams Dictionary to automatically identify and group distinct word senses into a computational inventory.

In practice

• Automate lexicographical data extraction.
• Improve Sanskrit word sense disambiguation.
• Develop semantic resources for NLP.

Topics

• Computational Linguistics
• Sanskrit NLP
• Sense Inventory
• Clustering Techniques
• Lexicography Automation
• Word Sense Disambiguation

Best for: AI Scientist, NLP Engineer, Research Scientist

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Editorial summary, takeaway, and curation by AIssential. Original article published by Paper Index on ACL Anthology.