Morphological analysis and disambiguation is crucial for natural language processing of morphologically rich languages. Enormous effort is required to collect accurate morphological parses in low resource settings such as the case of Kinyarwanda verbal forms. In this work, we propose and evaluate a method for morphological disambiguation of Kinyarwanda verbal forms using inflection:stem pairs provided by human annotators through a crowd-sourcing effort. We use two level morphological analysis, feature engineering and a maximum entropy classifier to effectively disambiguate morphological segmentations produced by the analyzer, achieving 89% accuracy without phrasal context.

Morphological Disambiguation from Stemming Data

POSTERS17: Morphology and Segmentation

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COLING, the International Conference on Computational Linguistics, is one of the premier conferences for natural language processing and computational linguistics. Often grouped within the field of artificial intelligence, but actually pre-dating the development of artificial intelligence, advances in computational linguistics and natural language processing are now some of the major drivers behind the use of artificial intelligence for commercial and social applications – for example, on-line search, machine translation and with voice-assisted conversational devices.

First established in 1965, the biennial COLING conference is held in diverse parts of the globe and attracts participants from both top-ranked research centers and emerging countries. Today, the most important developments in our field are taking place not only in universities and academic research institutes, but also in industrial research departments and in technological startups. COLING conferences provide opportunities for all these communities to showcase their exciting developments.

COLING 2020

COLING, the International Conference on Computational Linguistics, is one of the premier conferences for natural language processing and computational linguistics. Often grouped within the field of artificial intelligence, but actually pre-dating the development of artificial intelligence, advances in computational linguistics and natural language processing are now some of the major drivers behind the use of artificial intelligence for commercial and social applications – for example, on-line search, machine translation and with voice-assisted conversational devices.

Antoine Nzeyimana

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Morphological Disambiguation from Stemming Data

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