Date of Award
5-2022
Document Type
Thesis (Undergraduate)
Department or Program
Cognitive Science
First Advisor
Jonathan Phillips
Second Advisor
Soroush Vosoughi
Abstract
In this paper I evaluate the ability of different Natural Language Processing (NLP)
techniques to make human-like word relatedness judgements in a variant of the word-based board game Codenames. I analyze a variety of statistical and knowledge based approaches, combinations of these, and techniques for incorporating the wider game context into relatedness judgements. While no approach explored here reaches human performance, simple word embedding based approaches incorporate a surprising amount of the useful information captured by other techniques. I attempt to characterize the limitations of these approaches in relation to human game play, although differences are largely not systematic. Finally, I discuss these results in terms of future directions for the field of NLP.
Recommended Citation
Mills, Tracey, "Probing NLP Conceptual Relatedness Judgments Through the Word-Based Board Game Codenames" (2022). Dartmouth College Undergraduate Theses. 271.
https://digitalcommons.dartmouth.edu/senior_theses/271
