METHOD FOR SAMPLE AUGMENTATION

Provided are a method and an apparatus for sample augmentation relate to fields of a knowledge graph and natural language processing. The method includes: acquiring a second sample corpus and second triplet information of the second sample corpus by performing data augmentation on a first sample corpus labeled with first triplet information; acquiring third triplet information of a third sample corpus by performing semi-supervised learning on the third sample corpus without triplet information; and generating a set of training corpora for a triplet information extraction network based on the first sample corpus and the first triplet information, the second sample corpus and the second triplet information, and the third sample corpus and the third triplet information. A relatively high quality corpus may be generated in case of a few sample corpora, which reduces semantic loss, improves an extraction effect of triplet information, without labeling a large number of sample corpora.