QUESTION ANSWERING SYSTEM UPON UNIFIED LANGUAGE MODEL AND EVALUATING PERFORMANCE OF DATASETS

Abstract

Present days require automation and optimization in simple
but urgent tasks. It is granted to use opportunities of technologies and science in
order to work efficiently and to stay productive. In this paper, I seek to
understand opportunities and drawbacks of the publicly available datasets, such
as SQuAD, TriviaQA, Natural Questions (NQ), QuAC, NewsQA. It is vital to
choose a suitable dataset in order to create a system with better performance.
Specifically, the paper proposes an automatic question creating system that uses
state-of-the-art Natural Language Processing (NLP) - Unified Language Model
(UniLM). The question generating algorithm was verified using best datasets,
and it has shown noteworthy results - questions generated were logical and
correct. This study is important for teachers, teacher assistants, to save time
writing test questions and spend it for more important duties.