SubmissionNumber#=%=#5
FinalPaperTitle#=%=#StFX-NLP at SemEval-2024 Task 9: BRAINTEASER: Three Unsupervised Riddle-Solvers
ShortPaperTitle#=%=#
NumberOfPages#=%=#6
CopyrightSigned#=%=#Ethan Heavey
JobTitle#==#
Organization#==#St. Francis Xavier University
4130 University Ave
Antigonish, NS
Canada 
B2G 2W5
Abstract#==#In this paper, we explore three unsupervised learning models that we applied to Task 9: BRAINTEASER of SemEval 2024. Two of these models incorporate word sense disambiguation and part-of-speech tagging, specifically leveraging SensEmBERT and the Stanford log-linear part-of-speech tagger. Our third model relies on a more traditional language modelling approach. The best performing model, a bag-of-words model leveraging word sense disambiguation and part-of-speech tagging, secured the 10th spot out of 11 places on both the sentence puzzle and word puzzle subtasks.
Author{1}{Firstname}#=%=#Ethan
Author{1}{Lastname}#=%=#Heavey
Author{1}{Username}#=%=#penguins
Author{1}{Email}#=%=#ethanheavey@outlook.com
Author{1}{Affiliation}#=%=#St. Francis Xavier University
Author{2}{Firstname}#=%=#James
Author{2}{Lastname}#=%=#Hughes
Author{2}{Email}#=%=#jhughes@stfx.ca
Author{2}{Affiliation}#=%=#St. Francis Xavier University
Author{3}{Firstname}#=%=#Milton
Author{3}{Lastname}#=%=#King
Author{3}{Username}#=%=#kingm
Author{3}{Email}#=%=#mking@stfx.ca
Author{3}{Affiliation}#=%=#St. Francis Xavier University

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