MEBCK from Web using NLP Techniques

Abstract

The real life intelligent applications such as agents, expert systems, dialog understanding systems, weather forecasting systems, robotics etc. mainly focus on commonsense knowledge And basically these works on the knowledgebase which contains large amount of commonsense knowledge. The main intention of this work is to create a commonsense knowledge base by using an effective methodology to retrieve commonsense knowledge from large amount of web data. In order to achieve the best results, it makes use of different natural language processing techniques such as semantic role labeling, lexical and syntactic analysis.

Keywords: Automatic statistical semantic role tagger (ASSERT), lexico - syntactic pattern matching, semantic role labeling (SRL)