Thematic Role Extraction Using Shallow Parsing
Extracting thematic (semantic) roles is one of the
major steps in representing text meaning. It refers to finding the
semantic relations between a predicate and syntactic constituents in a
sentence. In this paper we present a rule-based approach to extract
semantic roles from Persian sentences. The system exploits a twophase
architecture to (1) identify the arguments and (2) label them
for each predicate.
For the first phase we developed a rule based shallow parser to
chunk Persian sentences and for the second phase we developed a
knowledge-based system to assign 16 selected thematic roles to the
chunks. The experimental results of testing each phase are shown at
the end of the paper.
Natural Language Processing, Semantic RoleLabeling, Shallow parsing, Thematic Roles.