This paper introduces a new task - Chinese address parsing - the task of mapping Chinese addresses into semantically meaningful chunks. While it is possible to model this problem using a conventional sequence labelling approach, our observation is that there exist complex dependencies between labels that cannot be readily captured by a simple linear-chain structure. We investigate neural structured prediction models with latent variables to capture such rich structural information within Chinese addresses. We create and publicly release a new dataset consisting of 15,000 Chinese addresses, and conduct extensive experiments on the dataset to investigate the model effectiveness and robustness.
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