Madeline Solis de Ovando
2026
Kelvi: A Morphological Parser to Support Tamil Literacy
Shankhalika Srikanth | Sabrina Yu | Sophia Chan | Madeline Solis de Ovando
Proceedings of the 21st Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2026)
Shankhalika Srikanth | Sabrina Yu | Sophia Chan | Madeline Solis de Ovando
Proceedings of the 21st Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2026)
We discuss the development of kelvi.ca, an open source web-based dictionary and morphological parser designed to aid Tamil learners in developing their literacy skills. Tamil is an agglutinative language and heavily suffixal. Existing Tamil dictionaries only carry stems, not conjugated or inflected forms, and for a beginner learner of the language, isolating the stem in an unfamiliar word can be very challenging. Kelvi provides 1) the stem of any input word alongside its definition, and 2) non-technical descriptions of any suffixes that are part of this input, so that learners will gradually start to recognize these suffixes and be able to understand and produce new Tamil words themselves. In detailing our process of collaborative research, user interviews, suffix database creation, and error analysis, we also hope to show that Kelvi can be adapted for other languages and has the potential to be a useful pedagogical aid for learner literacy development, especially for agglutinative and/or polysynthetic languages which tend to be otherwise underserved in the mainstream.