Building a Large Chinese Corpus Annotated with Semantic Dependency

Abstract

At present most of corpora are annotated mainly with syntactic knowledge. In this paper, we attempt to build a large corpus and annotate semantic knowledge with dependency grammar. We believe that words are the basic units of semantics, and the structure and meaning of a sentence consist mainly of a series of semantic dependencies between individual words. A 1,000,000-word-scale corpus annotated with semantic dependency has been built. Compared with syntactic knowledge, semantic knowledge is more difficult to annotate, for ambiguity problem is more serious. In the paper, the strategy to improve consistency is addressed, and congruence is defined to measure the consistency of tagged corpus.. Finally, we will compare our corpus with other well-known corpora.