Resumen

NUNSANGA, Morrel V. L.; PAKRAY, Partha; LALLAWMSANGA, C.  y  SINGH, L. Lolit Kumar. Part-of-Speech Tagging for Mizo Language Using Conditional Random Field. Comp. y Sist. [online]. 2021, vol.25, n.4, pp.803-812.  Epub 28-Feb-2022. ISSN 2007-9737.  https://doi.org/10.13053/cys-25-4-4044.

Part of speech (POS) tagging assigns a class or tag to each token in a sentence. The tag allocated to a word is mainly its part of speech or any other class of interest. Several applications of Natural Language Processing (NLP) require it as a prerequisite. The development of part-of-speech tagging for the under-resourced Mizo language is presented in this study, which makes use of a stochastic model known as Conditional Random Field (CRF). The CRF is a discriminative probabilistic classifier that considers both the context of a given word and the tag transition probabilities in the training dataset. A corpus of approximately 30,000 words was collected and manually annotated with the proposed tagset for system evaluation. On various sizes of training and test sets, the tagger achieved 89.46 % accuracy, 89.3 % F1-score, 89.42 % precision, and 89.48 % recall.

Palabras llave : Mizo POS tagging; conditional random field; Mizo part of speech tagger; computational linguistics.

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