The More Detail, the Better? – Investigating the Effects of Semantic Ontology Specificity on Vector Semantic Classification with a Plains Cree / nêhiyawêwin Dictionary
Daniel Dacanay, Atticus G. Harrigan, Arok Wolvengrey, Antti Arppe · 2021
One problem in the task of automatic semantic classification is the problem of determining the level on which to group lexical items.This is often accomplished using already existing, hierarchical semantic ontologies.The following investigation explores the computational assignment of semantic classifications on the contents of a dictionary of nêhiyawêwin / Plains Cree (ISO: crk, Algonquian, Western Canada and United States), using a semantic vector space model, and following two semantic ontologies, WordNet and SIL's Rapid Words, and compares how these computational results compare to manual classifications with the same two ontologies.