The dependence analysis is usually the key for improving the performance of text retrieval. Compared with the statistical value of a conceptual relationship, the recognition of relation type between concepts is more meaningful. In this paper, we explored a bootstrapping method for automatically extracting semantic patterns from a large-scale corpus to identify the geographical "be part of relationship between Chinese location concepts in contexts. Our contributions different from other bootstrapping methods lie in: (1) introducing a bi-sequence alignment algorithm in bio-informatics to generating candidate patterns, and (2) giving a new evaluating metric for patterns' confidence to enhance their extracting qualities in next iteration. In terms of automatic recognition of "be part of relationship, the experiments showed that the pattern set generated by our method achieves higher coverage and precision than DIPRE does.
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