Leveraging English Word Embeddings for Semi-Automatic Semantic Classification in Nêhiyawêwin (Plains Cree)

Atticus Harrigan, Antti Arppe


Abstract
This paper details a semi-automatic method of word clustering for the Algonquian language, Nêhiyawêwin (Plains Cree). Although this method worked well, particularly for nouns, it required some amount of manual postprocessing. The main benefit of this approach over implementing an existing classification ontology is that this method approaches the language from an endogenous point of view, while performing classification quicker than in a fully manual context.
Anthology ID:
2021.americasnlp-1.12
Volume:
Proceedings of the First Workshop on Natural Language Processing for Indigenous Languages of the Americas
Month:
June
Year:
2021
Address:
Online
Editors:
Manuel Mager, Arturo Oncevay, Annette Rios, Ivan Vladimir Meza Ruiz, Alexis Palmer, Graham Neubig, Katharina Kann
Venue:
AmericasNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
113–121
Language:
URL:
https://aclanthology.org/2021.americasnlp-1.12
DOI:
10.18653/v1/2021.americasnlp-1.12
Bibkey:
Cite (ACL):
Atticus Harrigan and Antti Arppe. 2021. Leveraging English Word Embeddings for Semi-Automatic Semantic Classification in Nêhiyawêwin (Plains Cree). In Proceedings of the First Workshop on Natural Language Processing for Indigenous Languages of the Americas, pages 113–121, Online. Association for Computational Linguistics.
Cite (Informal):
Leveraging English Word Embeddings for Semi-Automatic Semantic Classification in Nêhiyawêwin (Plains Cree) (Harrigan & Arppe, AmericasNLP 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.americasnlp-1.12.pdf