A Description of ZZ_INFO_TECH System at KBP 2013
نویسندگان
چکیده
In this paper, we report the participation of ZZ_INFO_TECH team in entity linking task for Knowledge Base Population at Text Analysis Conference 2013. Our team submitted 4 runs for this evaluation task. In our system, we adopts some simple heuristic rules and context similarity to filter irrelevant candidates; extracts multiple features and trains SVM Ranking model to realize candidate ranking; computes five common statistics and trains SVM model to identify NIL query.
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تاریخ انتشار 2013