UTtoKB: a Model for Semantic Relation Extraction from Unstructured Text

Abstract

In this paper, a model prototype called UTtoKB has been built. It extracts semantic relationships from an unstructured text based on ontology. The model is a pipeline steps based on natural language processing (NLP) tasks and tools like Coreference Resolution (CR), Named Entity Recognition (NER), Semantic Role Labeling (SRL), and Part of Speech (PoS) Tagging. WordNet is the tool used to measure similarities between entities to convert them into ontology concepts and properties. The model works fine in specific domains, while performance degrades in other domains due to the instability of WordNet performance in finding semantic similarities.