Papers by Omnia Zayed
Figure Me Out: A Gold Standard Dataset for Metaphor Interpretation (2020.lrec-1)
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| Challenge: | Metaphor comprehension and understanding is a complex cognitive task that requires interpreting metaphors by grasping the interaction between the meaning of their target and source concepts. |
| Approach: | They propose an automatic retrieval approach to annotate verb-noun metaphors in text . they validated their approach by annotating around 1,500 metaphors from tweets . |
| Outcome: | The proposed method reduces the workload on annotators and maintains consistency . it can be used to interpret verb-noun metaphoric expressions in tweets . |
Contextual Modulation for Relation-Level Metaphor Identification (2020.findings-emnlp)
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| Challenge: | Existing approaches to identifying metaphors in text ignore context where metaphor occurs . existing approaches focus on word-level identification without explicitly modelling interaction between metaphor components . |
| Approach: | They propose a method for identifying relation-level metaphoric expressions of certain grammatical relations based on contextual modulation. |
| Outcome: | The proposed architecture achieves state-of-the-art results on benchmark datasets. |
LUCE: A Dynamic Framework and Interactive Dashboard for Opinionated Text Analysis (2025.coling-demos)
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| Challenge: | LUCE is an advanced dynamic framework for analysing opinionated text . it features computational modules for different elements of opinions, e.g., sentiment/emotion, suggestion, figurative language, hate/toxic speech, and topics. |
| Approach: | They introduce a dynamic framework with an interactive dashboard for analysing opinionated text . it features computational modules of text classification and extraction for different elements of opinions . |
| Outcome: | The framework is validated in a relevant environment and its capabilities and performance demonstrated . it features trained models, python-based APIs, and a user-friendly dashboard . |
A Hybrid Approach to Aspect Based Sentiment Analysis Using Transfer Learning (2024.lrec-main)
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| Challenge: | Aspect-Based Sentiment Analysis (ABSA) aims to identify terms or multiword expressions (MWEs) on which sentiments are expressed and the sentiment polarities associated with them. |
| Approach: | They propose a hybrid approach to Aspect-Based Sentiment Analysis using transfer learning . they exploit the strengths of large language models and traditional syntactic dependencies . |
| Outcome: | The proposed method exploits the strengths of large language models and traditional syntactic dependencies. |