Computational Analysis versus Human Intuition: A Critical Comparison of Vector Semantics with Manual Semantic Classification in the Context of Plains Cree

Abstract

A persistent challenge in the creation of semantically classified dictionaries and lexical resources is the lengthy and expensive process of manual semantic classification, a hindrance which can make adequate semantic resources unattainable for under-resourced language communities. We explore here an alternative to manual classification using a vector semantic method, which, although not yet at the level of human sophistication, can provide usable first-pass semantic classifications in a fraction of the time. As a case example, we use a dictionary in Plains Cree (ISO: crk, Algonquian, Western Canada and United States)