Using FRED for Named Entity Resolution, Linking and Typing for Knowledge Base Population

被引：12
|
作者：
Consoli, Sergio [1 ]
Recupero, Diego Reforgiato [1 ]
机构：
[1] CNR, ISTC, STLab, Catania, Italy
来源：
SEMANTIC WEB EVALUATION CHALLENGES | 2015年 / 548卷
关键词：
D O I：
10.1007/978-3-319-25518-7_4
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
FRED is a machine reader for extracting RDF graphs that are linked to LOD and compliant to Semantic Web and Linked Data patterns. We describe the capabilities of FRED as a semantic middleware for semantic web applications. In particular, we will show (i) how FRED recognizes and resolves named entities, (ii) how it links them to existing knowledge base, and (iii) how it gives them a type. Given a sentence in any language, it provides different semantic functionalities (frame detection, topic extraction, named entity recognition, resolution and coreference, terminology extraction, sense tagging and disambiguation, taxonomy induction, semantic role labeling, type induction) by means of a versatile user-interface, which can be recalled as REST Web service. The system can be freely used at http://wit.istc.cnr.it/stlab-tools/fred.
引用
收藏
页码：40 / 50
页数：11
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