Named Entities Recognition in Computer Field for Entity Attribute Semantic Knowledge Database

Abstract

To construct the entity attribute semantic knowledge database in computer field, we need to achieve the relationship between the entities and attributes. That requires to identify the computer-named entities that present in the real text. Moreover, the verb collocation templates that describe the relationships would be achieved. In this paper, the necessary knowledge to recognize entities would be integrated into a generic framework by using entity-attribute concept. Thereby, the rules of entity recognition would be simplified. We transform the named entities recognition process of computer entities into an labeling process. For the given text to be processed, match the possible brand words or serial words driven by the brand attribute value and the series attribute value. Then the model sequence or the abstract entity suffix can be matched and marked in the text which successfully marked the brand or series. Finally, match the results of the annotation with the recognition rules, and output the marking sequence which accord with the rules as computer entity word. Proceed from the idea of entity-attribute- framework, the name of an entity is the combination of the word mapping of the entity's particular attribute value and the word mapping of the conceptual entity to which the entity belongs. By writing the specified entity naming rules in such way, it is possible to organically integrate the rules with the instantiation of supporting rules into the knowledge network centered on entities, instead of forming irrelevant dictionary knowledge that is only isolated for specific tasks only. Experimental result showed that the system achieved the F1 measure of 86.1%.