  Coordinate relation refers to the relation between instances of a concept and
the relation between the directly hyponyms of a concept. In this paper, we
focus on the task of extracting terms which are coordinate with a user given
seed term in Chinese, and grouping the terms which belong to different concepts
if the seed term has several meanings. We propose a semi-supervised method that
integrates manually defined linguistic patterns and automatically learned
semi-structural patterns to extract coordinate terms in Chinese from web search
results. In addition, terms are grouped into different concepts based on their
co-occurring terms and contexts. We further calculate the saliency scores of
extracted terms and rank them accordingly. Experimental results demonstrate
that our proposed method generates results with high quality and wide coverage.
