Kernel-based supervised methods such as dependency tree kernels (Culotta and Sorensen, 2004), subsequence kernels (Bunescu and Mooney, 2006) and convolution tree kernels (Qian et al., 2008) have been rather successful in learning this task.
purely supervised relation extraction methods assume the availability of sufficient labeled data, which may be costly to obtain for new domains.