  Person knowledge extraction is the foundation of the Tibetan knowledge graph
construction, which provides support for Tibetan question answering system,
information retrieval, information extraction and other researches, and
promotes national unity and social stability. This paper proposes a SVM and
template based approach to Tibetan person knowledge extraction. Through
constructing the training corpus, we build the templates based the shallow
parsing analysis of Tibetan syntactic, semantic features and verbs. Using the
training corpus, we design a hierarchical SVM classifier to realize the entity
knowledge extraction. Finally, experimental results prove the method has
greater improvement in Tibetan person knowledge extraction.
