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Extraction of predicate-argument structure from sentence based on PICO frames
Suwarningsih W.a,b, Purwarianti A.a, Supriana I.a
a School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Indonesia
b Research Center for Informatics, Indonesian Institute of Science, Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2015 IEEE.Identifying a logical relation between sentences and semantic role labelling requires a deeper knowledge of recognizing the relationship of various expressions. One method that can be used is by means of the extraction of predicate argument structure. This paper is purposely to describe a new automatic method for the extraction of Indonesian medical predicate-argument (P-A) structure analysis based upon PICO frame. Learning some relevant features, the method assigns some case roles (such as Problem/Population/Patient, Intervention, Compare/Control and Outcome) to the argument of the target predicate using the features of the words that are located closest to the target predicate. In this paper the illustration of their use in a pattern-based relation extraction component of PICO frame has been described. It is indicated from the test results that the use of the features with more semantic role categories in determining the P-A structure represents the respective results reaching at 89.35% for precision, 89.12% for recall and 89.98% for F1.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Argument structures,Indonesian medical sentences,Logical relations,PICO frame,Relation extraction,Relevant features,Semantic roles,Structure analysis[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Indonesian medical sentences,PICO frame,predicate-argument structure,semantic role category[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/ICACOMIT.2015.7440182[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]