A segment-based annotation tool for Korean treebanks with minimal human intervention

In this paper, we propose a segment-based annotation tool providing appropriate interactivity between a human annotator and an automatic parser. The proposed annotation tool provides the preview of a complete sentence structure suggested by the parser, and updates the preview whenever the annotator cancels or selects each segmentation point. Thus, the annotator can select the proper sentence segments maximizing parsing accuracy and minimizing human intervention. Experimental results show that the proposed tool allows the annotator to be able to reduce human intervention by approximately 39% compared with manual annotation. Sejong Korean treebank, one of the large scale treebanks, was constructed with the proposed annotation tool.