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Rule-based Indonesian Open Information Extraction
Romadhony A.a, Purwarianti A.a, Widyantoro D.H.a
a School of Electrical Engineering and Informatics, Institute of Technology Bandung, 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]© 2018 IEEE.Open Information Extraction (Open IE) is a paradigm that tries to extract as much information as possible, with less restriction on the information type to be extracted. It extracts relation tuples, in which a relation tuple consists of a relation tuple trigger and several relation arguments. Previous studies on developing Open IE systems have mainly been for English. Recently, several works have also been carried out in other languages, but there is no study on Open IE for Indonesian. In this paper, we investigate several rule-based methods for building an Open IE system for Indonesian. We use lexical and syntactic features that were obtained from an Indonesian language processing tool and compare the extraction results against the standard English Open IE systems. The experimental results for English-Indonesian parallel sentences show that the POSTag+Noun Phrase-based rules have better performance. At the same time, the dependency relation-based performance depends on the dependency parser performance, which still needs improvement since we use a small size dataset on training the parser. However, both approaches show good performance in identifying the relation tuple trigger, with the recall score being 0.96 for the POSTag+Noun Phrase-based rules and 0.6 for the POSTag+Dependency relation based-rules.[/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]Dependency relation,Indonesian languages,Indonesians,Information types,Noun phrase,Rule based,Rule-based method,Syntactic features[/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 Open IE system,Open Information Extraction,POSTag and dependency relation-based,POSTag and Noun Phrase-based,rule-based[/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/ICAICTA.2018.8541293[/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]