Bayesian Networks is a model that efficiently represents knowledge and probabilistic inference and is a popular graphics decision-making analysis tool.

Concerning the difficulties in part-of-speech tagging in English present participle, the authors analyzed the drawbacks of Hidden Markov Models (HMM) and proposed Bayesian decision tree model.

Results We demonstrate that the Bayesian information criterion and decision theory are the most appropriate model-selection criteria because of their high accuracy and precision.