An Evaluation of Techniques for Classification of Conditional Sentences and Their Structural Components

Abstract

Conditional statements are an important part of procedural knowledge as they determine the decision points in the control flow. In order to bootstrap conversation bots and automation tools automatically from natural language procedure documents, it is important to be able to classify the conditional statements accurately and separate the condition and effect correctly. This paper aims at exploring three different techniques to classify and analyze conditional statements and discusses the advantages and drawbacks of each of them. This paper also aims at understanding the drawbacks of the three techniques and overcoming them by building models with better performance.