In this paper we propose a general methodology for designing semantic role/
relation system Based on this methodology we establish a succinct semantic
relation system for consecutive predicative constituents for Chinese which
includes serial verb construction discourse construction and other constructions
describing serial events This semantic relation system has 13 middle-level classes
and 24 fine-grained sub-classes in contrast to conventional complex classification
schemes and meets the uniqueness and completeness criteria of semantic relation
identification We conduct experiments on our system by training four annotators
in 1 h to label 200 sentences extracted from Sinica Treebank and HIT-CDTB. With
the help of our predesigned feature-based decision tree and a connective markers
checklist, the annotators attain a 73% consistency with the reference standard annotation
and substantial agreement by Cohen’s kappa coefficient for middle-level labeling. By
analyzing the labeling error type we slightly revise our classification scheme and
propose six methods to improve the classification and labeling system hoping to
achieve even better agreement in the future.

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• Semantic relation identification for consecutive predicative constituents in Chinese