@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},
	}