Khmer Treebank Construction via Interactive Tree Visualization

Abstract

Despite the fact that there are a number of researches working on Khmer Language in the field of Natural Language Processing along with some resources regarding words segmentation and POS Tagging, we still lack of high-level resources regarding syntax, Treebanks and grammars, for example. This paper illustrates the semi-automatic framework of constructing Khmer Treebank and the extraction of the Khmer grammar rules from a set of sentences taken from the Khmer grammar books. Initially, these sentences will be manually annotated and processed to generate a number of grammar rules with their probabilities once the Treebank is obtained. In our experiments, the annotated trees and the extracted grammar rules are analyzed in both quantitative and qualitative way. Finally, the results will be evaluated in three evaluation processes including Self-Consistency, 5-Fold Cross-Validation, Leave-One-Out Cross-Validation along with the three validation methods such as Precision, Recall, F1-Measure. According to the result of the three validations, Self-Consistency has shown the best result with more than 92%, followed by the Leave-One-Out Cross-Validation and 5-Fold Cross Validation with the average of 88% and 75% respectively. On the other hand, the crossing bracket data shows that Leave-One-Out Cross Validation holds the highest average with 96% while the other two are 85% and 89%, respectively.