# Neural Metaphor Detection in Context

arXiv: https://arxiv.org/abs/1808.09653 · HTML: https://mlsanity.com/paper/1808.09653/

## Key facts

- Cited by 34 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Aug 2018.

## Built on by (most cited first, 30 of 34)

- [Can Large Language Models Transform Computational Social Science?](https://mlsanity.com/paper/2305.03514/) (2023)
- [Testing the Ability of Language Models to Interpret Figurative Language](https://mlsanity.com/paper/2204.12632/) (2022)
- [RiddleSense: Reasoning about Riddle Questions Featuring Linguistic Creativity and Commonsense Knowledge](https://mlsanity.com/paper/2101.00376/) (2021)
- [MERMAID: Metaphor Generation with Symbolism and Discriminative Decoding](https://mlsanity.com/paper/2103.06779/) (2021)
- [MelBERT: Metaphor Detection via Contextualized Late Interaction using Metaphorical Identification Theories](https://mlsanity.com/paper/2104.13615/) (2021)
- [Investigating Robustness of Dialog Models to Popular Figurative Language Constructs](https://mlsanity.com/paper/2110.00687/) (2021)
- [FrameBERT: Conceptual Metaphor Detection with Frame Embedding Learning](https://mlsanity.com/paper/2302.04834/) (2023)
- [BRAINTEASER: Lateral Thinking Puzzles for Large Language Models](https://mlsanity.com/paper/2310.05057/) (2023)
- [Crossing the Conversational Chasm: A Primer on Natural Language Processing for Multilingual Task-Oriented Dialogue Systems](https://mlsanity.com/paper/2104.08570/) (2021)
- [ePiC: Employing Proverbs in Context as a Benchmark for Abstract Language Understanding](https://mlsanity.com/paper/2109.06838/) (2021)
- [Metaphor Detection with Effective Context Denoising](https://mlsanity.com/paper/2302.05611/) (2023)
- [Metaphor Detection via Explicit Basic Meanings Modelling](https://mlsanity.com/paper/2305.17268/) (2023)
- [A Computational Framework for Slang Generation](https://mlsanity.com/paper/2102.01826/) (2021)
- [Adversarial Multi-task Learning for End-to-end Metaphor Detection](https://mlsanity.com/paper/2305.16638/) (2023)
- [Construction Artifacts in Metaphor Identification Datasets](https://mlsanity.com/paper/2311.00790/) (2023)
- [When People are Floods: Analyzing Dehumanizing Metaphors in Immigration Discourse with Large Language Models](https://mlsanity.com/paper/2502.13246/) (2025)
- [How Metaphors Impact Political Discourse: A Large-Scale Topic-Agnostic Study Using Neural Metaphor Detection](https://mlsanity.com/paper/2104.03928/) (2021)
- [Ring That Bell: A Corpus and Method for Multimodal Metaphor Detection in Videos](https://mlsanity.com/paper/2301.01134/) (2022)
- [Multilingual Multi-Figurative Language Detection](https://mlsanity.com/paper/2306.00121/) (2023)
- [Looking Beyond the Obvious: A Survey on Abstract Concept Recognition for Video Understanding](https://mlsanity.com/paper/2508.20765/) (2025)
- [Impact of Target Word and Context on End-to-End Metonymy Detection](https://mlsanity.com/paper/2112.03256/) (2021)
- [An Expectation-Realization Model for Metaphor Detection](https://mlsanity.com/paper/2311.03963/) (2023)
- [PINEAPPLE: Personifying INanimate Entities by Acquiring Parallel Personification data for Learning Enhanced generation](https://mlsanity.com/paper/2209.07752/) (2022)
- [Curriculum-style Data Augmentation for LLM-based Metaphor Detection](https://mlsanity.com/paper/2412.02956/) (2024)
- [Combining Pre-trained Word Embeddings and Linguistic Features for Sequential Metaphor Identification](https://mlsanity.com/paper/2104.03285/) (2021)
- [On the Impact of Temporal Representations on Metaphor Detection](https://mlsanity.com/paper/2111.03320/) (2021)
- [HYU at SemEval-2022 Task 2: Effective Idiomaticity Detection with Consideration at Different Levels of Contextualization](https://mlsanity.com/paper/2206.11854/) (2022)
- [Metaphorical Paraphrase Generation: Feeding Metaphorical Language Models with Literal Texts](https://mlsanity.com/paper/2210.04756/) (2022)
- [Deep Learning-Based Knowledge Injection for Metaphor Detection: A Comprehensive Review](https://mlsanity.com/paper/2308.04306/) (2023)
- [Enhancing Metaphor Detection through Soft Labels and Target Word Prediction](https://mlsanity.com/paper/2403.18253/) (2024)

## Abstract (arXiv)

We present end-to-end neural models for detecting metaphorical word use in context. We show that relatively standard BiLSTM models which operate on complete sentences work well in this setting, in comparison to previous work that used more restricted forms of linguistic context. These models establish a new state-of-the-art on existing verb metaphor detection benchmarks, and show strong performance on jointly predicting the metaphoricity of all words in a running text.