Intelligent information extraction using logical approach: skolemize clauses binding

This paper is concerned with the problem of generating an automated information extraction in the context of logical knowledge representation, reasoning, and inferential processing. The research focused on Wh types of question to a restricted domain. Here, an existing resolution theorem prover with the modification of some components was adapted based on experiments carried out such as: knowledge representation, and automated information answer generation. Based on that, a Pragmatic Skolemize Clauses representation used to represent the semantic formalism for the computational linguistic was designed. The process of reasoning in generating automated information began with the execution of resolution theorem proving. Then, the answer extraction was proceed with skolemize clauses binding approach to continue tracking the relevant semantic relation rules in knowledge base, which contained the answer key in skolem constant form that can be bounded. The complete relevant information is defined as a set of skolemize clauses containing at least one skolem constant that is shared and bound to each other.

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