Frame Identification as Categorization: Exemplars vs Prototypes in Embeddingland

Jennifer Sikos, Sebastian Padó


Abstract
Categorization is a central capability of human cognition, and a number of theories have been developed to account for properties of categorization. Even though many tasks in semantics also involve categorization of some kind, theories of categorization do not play a major role in contemporary research in computational linguistics. This paper follows the idea that embedding-based models of semantics lend themselves well to being formulated in terms of classical categorization theories. The benefit is a space of model families that enables (a) the formulation of hypotheses about the impact of major design decisions, and (b) a transparent assessment of these decisions. We instantiate this idea on the task of frame-semantic frame identification. We define four models that cross two design variables: (a) the choice of prototype vs. exemplar categorization, corresponding to different degrees of generalization applied to the input; and (b) the presence vs. absence of a fine-tuning step, corresponding to generic vs. task-adaptive categorization. We find that for frame identification, generalization and task-adaptive categorization both yield substantial benefits. Our prototype-based, fine-tuned model, which combines the best choices for these variables, establishes a new state of the art in frame identification.
Anthology ID:
W19-0425
Volume:
Proceedings of the 13th International Conference on Computational Semantics - Long Papers
Month:
May
Year:
2019
Address:
Gothenburg, Sweden
Editors:
Simon Dobnik, Stergios Chatzikyriakidis, Vera Demberg
Venue:
IWCS
SIG:
SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
295–306
Language:
URL:
https://aclanthology.org/W19-0425
DOI:
10.18653/v1/W19-0425
Bibkey:
Cite (ACL):
Jennifer Sikos and Sebastian Padó. 2019. Frame Identification as Categorization: Exemplars vs Prototypes in Embeddingland. In Proceedings of the 13th International Conference on Computational Semantics - Long Papers, pages 295–306, Gothenburg, Sweden. Association for Computational Linguistics.
Cite (Informal):
Frame Identification as Categorization: Exemplars vs Prototypes in Embeddingland (Sikos & Padó, IWCS 2019)
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PDF:
https://aclanthology.org/W19-0425.pdf