Determination of referential property and number of nouns in Japanese sentences for machine translation into English

TL;DR

This paper presents a method for estimating the referential property and number of Japanese nouns to improve machine translation into English, achieving high accuracy with rule-based classification.

Contribution

It introduces a rule-based approach to classify Japanese nouns' referential property and number, enabling more accurate translation into English.

Findings

Achieved 85.5% accuracy in referential property estimation.

Achieved 89.0% accuracy in noun number estimation.

Rules generalized reasonably well to new texts with 68.9% and 85.6% accuracy.

Abstract

When translating Japanese nouns into English, we face the problem of articles and numbers which the Japanese language does not have, but which are necessary for the English composition. To solve this difficult problem we classified the referential property and the number of nouns into three types respectively. This paper shows that the referential property and the number of nouns in a sentence can be estimated fairly reliably by the words in the sentence. Many rules for the estimation were written in forms similar to rewriting rules in expert systems. We obtained the correct recognition scores of 85.5\% and 89.0\% in the estimation of the referential property and the number respectively for the sentences which were used for the construction of our rules. We tested these rules for some other texts, and obtained the scores of 68.9\% and 85.6\% respectively.