@article{(Open Science Index):https://publications.waset.org/pdf/10674, title = {Thematic Role Extraction Using Shallow Parsing}, author = {Mehrnoush Shamsfard and Maryam Sadr Mousavi}, country = {}, institution = {}, abstract = {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.}, journal = {International Journal of Electrical and Computer Engineering}, volume = {2}, number = {6}, year = {2008}, pages = {2113 - 2119}, ee = {https://publications.waset.org/pdf/10674}, url = {https://publications.waset.org/vol/18}, bibsource = {https://publications.waset.org/}, issn = {eISSN: 1307-6892}, publisher = {World Academy of Science, Engineering and Technology}, index = {Open Science Index 18, 2008}, }