Use of Natural Language Inference in Optimizing Reviews and Providing Insights to end Consumers

Natural Language Inference or NLI adds extraordinary advantages to already existing Natural Language Processing use cases available. NLI has the potential to add syllogistic reasoning over the already existing facts and develop a new kind of knowledge dataset in itself. In this paper, we have demonstrated a Recognizing Textual Entailment wherein the task is to recognize whether a given hypothesis is true (Entailment), false (Contradiction) or unrelated(neutral) with respect to the sentence called premise. The task is performed by training MNLI corpus along with the manually collected dataset from Amazon Product Reviews each having hypothesis and premise pairs with corresponding labels. With this use case, we propose to bring sustainable development in the classification methods used by major E-commerce companies.