Abstract
Metaphors use words from one domain of knowledge to describe another, which can make the meaning less clear and require human interpretation to understand. This makes it difficult for automated models to detect metaphorical usage. The objective of the experiments in the paper is to enhance the ability of deep learning models to detect metaphors automatically. This is achieved by using two elements of semantic richness, sensory experience, and body-object interaction, as the main lexical features, combined with the contextual information present in the metaphorical sentences. The tests were conducted using classification and sequence labeling models for metaphor detection on the three metaphorical corpora VUAMC, MOH-X, and TroFi. The sensory experience led to significant improvements in the classification and sequence labelling models across all datasets. The highest gains were seen on the VUAMC dataset: recall increased by 20.9%, F1 by 7.5% for the classification model, and Recall increased by 11.66% and F1 by 3.69% for the sequence labelling model. Body-object interaction also showed positive impact on the three datasets.
Original language | English |
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Title of host publication | Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing |
Editors | Ruslan Mitkov, Galia Angelova |
Publisher | Incoma Ltd |
Pages | 80-89 |
Number of pages | 10 |
ISBN (Electronic) | 9789544520922 |
DOIs | |
Publication status | Published - 6 Sept 2023 |
Event | 2023 International Conference Recent Advances in Natural Language Processing: Large Language Models for Natural Language Processing, RANLP 2023 - Varna, Bulgaria Duration: 4 Sept 2023 → 6 Sept 2023 |
Publication series
Name | International Conference Recent Advances in Natural Language Processing |
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Publisher | Incoma Ltd |
ISSN (Print) | 1313-8502 |
ISSN (Electronic) | 2603-2813 |
Conference
Conference | 2023 International Conference Recent Advances in Natural Language Processing: Large Language Models for Natural Language Processing, RANLP 2023 |
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Country/Territory | Bulgaria |
City | Varna |
Period | 4/09/23 → 6/09/23 |
Bibliographical note
Publisher Copyright:© 2023 Incoma Ltd. All rights reserved.
ASJC Scopus subject areas
- Software
- Computer Science Applications
- Artificial Intelligence
- Electrical and Electronic Engineering