Abstract
AbstractCross-document entity disambiguation is the problem of identifying whether mentions from different documents refer to the same or distinct entities and rises in information fusion and automated knowledge base construction. In this paper, we describe a Chinese Information Extraction (IE) and fusion system based on Hadoop Framework, which involves document-level IE and corpus-level IE, a pipeline and multi-level modular approach to Name Entity Recognitions (EDR), entity relationship extraction and information fusion. In document-level IE, information associated with each mention of the name can be merged into rich profiles for entities based on our co-reference and alias modular, in corpus-level IE, entity disambiguation is performed based on agglomerative hierarchical clustering using Map Reduce. The visualized results of the entity centric information graph have been demonstrated.KeywordsInformation extractionInformation fusionNatural language processingInformation networkEntity disambiguationMap reduce
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