Unicorn Story Generation and Limits of Words - On Perspectives of Automatic Tacit Knowledge Addition

Abstract

In our paper we discuss the problem of tacit knowledge which probably is one of the biggest obstacles on the way to human-level language understanding. While the latest massive transformer-based NLP algorithms show the potential to generate natural text, translate and answer questions, these achievements are still insufficient to directly help machines to acquire common sense. We introduce the problem of tacit knowledge and various approaches to solving it by knowledge completion with automatic text generation which is meant to enrich existing texts and to improve machine learning process by filling the semantic gaps naturally omitted by human beings while generating a natural language. We present various types of knowledge additions we performed in the past and report on the latest achievements in Schankian scripts generation.