Natural language inference model for the Vietnamese language with machine learning algorithms: a view from “Truyen Kieu”

Abstract

Inference models in natural language predict whether a hypothesis sentence can be inferred from a premise sentence or not. Understanding the inference properties of natural language can elevate the representation of the semantics context. Many studies on this field are in English, but few are in Vietnamese. So, we introduce the Natural Language Inference corpus in Vietnamese using the Tale of Kieu, “Truyên Kiêu”, which Nguyên Du wrote. The dataset includes the premise of the poems in “Truyên Kiêu”; the hypothesis is that the conclusions are gathered from the “Kieu fortune-telling”. We make the following contributions: (i) provided the corpus for applying machine learning to semantic representation in the Vietnamese language; (ii) inference models in a natural language using machine learning method to predict the relationship between premise and hypothesis sentences. Finally, our research helps keep the traditional beauty of “Truyên Kiêu” in general and the culture of “Kieu fortune-telling” in particular.