Abstract
Figurative language (e.g., “he flew like the wind”) is challenging to understand, as it is hard to tell what implicit information is being conveyed from the surface form alone. We hypothesize that to perform this task well, the reader needs to mentally elaborate the scene being described to identify a sensible meaning of the language. We present DREAM-FLUTE, a figurative language understanding system that does this, first forming a “mental model” of situations described in a premise and hypothesis before making an entailment/contradiction decision and generating an explanation. DREAM-FLUTE uses an existing scene elaboration model, DREAM, for constructing its “mental model.” In the FigLang2022 Shared Task evaluation, DREAM-FLUTE achieved (joint) first place (Acc@60=63.3%), and can perform even better with ensemble techniques, demonstrating the effectiveness of this approach. More generally, this work suggests that adding a reflective component to pretrained language models can improve their performance beyond standard fine-tuning (3.3% improvement in Acc@60).
Original language | English |
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Title of host publication | FLP 2022 - 3rd Workshop on Figurative Language Processing, Proceedings of the Workshop |
Publisher | Association for Computational Linguistics (ACL) |
Pages | 84-93 |
Number of pages | 10 |
ISBN (Electronic) | 9781959429111 |
State | Published - 2022 |
Externally published | Yes |
Event | 3rd Workshop on Figurative Language Processing, FigLang 2022, as part of EMNLP 2022 - Abu Dhabi, United Arab Emirates Duration: 8 Dec 2022 → … |
Publication series
Name | FLP 2022 - 3rd Workshop on Figurative Language Processing, Proceedings of the Workshop |
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Conference
Conference | 3rd Workshop on Figurative Language Processing, FigLang 2022, as part of EMNLP 2022 |
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Country/Territory | United Arab Emirates |
City | Abu Dhabi |
Period | 8/12/22 → … |
Bibliographical note
Publisher Copyright:© 2022 Association for Computational Linguistics.