Research pair
Tawseef Ahmad Mir & Aadil Ahmad Lawaye
Alliance University, Bangalore · Baba Ghulam Shah Badshah University, Rajouri
The main body of work on Kashmiri word sense disambiguation: a sense-annotated corpus of about 19,854 sentences for 124 ambiguous words, built on Kashmiri WordNet, and a series of supervised classifiers trained on it.
- 3
- Papers
- 1
- Datasets
Focus
Papers 3
Word Sense Disambiguation Corpus for Kashmiri
The first standard WSD dataset for Kashmiri: a sense-annotated corpus covering 124 commonly used ambiguous Kashmiri words, drawn from a raw corpus of roughly 1 million tokens. Establishes the baseline resource for Kashmiri word sense disambiguation.
Naïve Bayes Classifier for Kashmiri Word Sense Disambiguation
Applies a Naïve Bayes classifier to Kashmiri word sense disambiguation on the authors' sense-annotated corpus.
Building Kashmiri Sense Annotated Corpus and its Usage in Supervised Word Sense Disambiguation
A sense-annotated Kashmiri corpus for lexical-sample word sense disambiguation, with Kashmiri WordNet senses, used to train and compare supervised classifiers.
Datasets 1
Worked with
- Parveen Rana
- Ghayas Ahmed
Every work above is a record in the Kashmiri NLP resource hub, credited as published; profile details come from doi.org. Something missing or wrong? Submit it.