Pattern Based Relation Extraction on Presian News Articles, M.Sc. Thesis Sharif University of Technology ; Bahrani, Mohammad (Supervisor) ; Sameti, Hossein (Co-Advisor)
Abstract
Relation extraction is known as a main task in information extraction. There are two main approach in this field, rule based and statistical approaches. This thesis applied a rule based relation extraction approach. In this research we tried to recognize Persian syntactic and morphological patterns to extract relation between named entities. At first we annotated a news dataset by person,organization and location named entity tags which is included more than 100 thousand tokens. After that we found there are 1037 relations 2197 candidate relations. Candidate and labled relations extracted between two entities which is located in a clause. These relations are "PERS_PERS-COMMENTING",...
Cataloging briefPattern Based Relation Extraction on Presian News Articles, M.Sc. Thesis Sharif University of Technology ; Bahrani, Mohammad (Supervisor) ; Sameti, Hossein (Co-Advisor)
Abstract
Relation extraction is known as a main task in information extraction. There are two main approach in this field, rule based and statistical approaches. This thesis applied a rule based relation extraction approach. In this research we tried to recognize Persian syntactic and morphological patterns to extract relation between named entities. At first we annotated a news dataset by person,organization and location named entity tags which is included more than 100 thousand tokens. After that we found there are 1037 relations 2197 candidate relations. Candidate and labled relations extracted between two entities which is located in a clause. These relations are "PERS_PERS-COMMENTING",...
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