mlsanityData to 14 Oct 2026

EPIE Dataset: A Corpus For Possible Idiomatic Expressions

arXiv 2006.09479 ↗First posted 16 Jun 2020cs.CL cs.LGcited by 24

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Abstract (arXiv)

Idiomatic expressions have always been a bottleneck for language comprehension and natural language understanding, specifically for tasks like Machine Translation(MT). MT systems predominantly produce literal translations of idiomatic expressions as they do not exhibit generic and linguistically deterministic patterns which can be exploited for comprehension of the non-compositional meaning of the expressions. These expressions occur in parallel corpora used for training, but due to the comparatively high occurrences of the constituent words of idiomatic expressions in literal context, the idiomatic meaning gets overpowered by the compositional meaning of the expression. State of the art Metaphor Detection Systems are able to detect non-compositional usage at word level but miss out on idiosyncratic phrasal idiomatic expressions. This creates a dire need for a dataset with a wider coverage and higher occurrence of commonly occurring idiomatic expressions, the spans of which can be used for Metaphor Detection. With this in mind, we present our English Possible Idiomatic Expressions(EPIE) corpus containing 25206 sentences labelled with lexical instances of 717 idiomatic expressions. These spans also cover literal usages for the given set of idiomatic expressions. We also present the utility of our dataset by using it to train a sequence labelling module and testing on three independent datasets with high accuracy, precision and recall scores.

Key facts. Cited by 24 papers in the map (data through 14 Oct 2026). First posted on arXiv 16 Jun 2020.

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Citing papers per year: 2021: 2; 2022: 1; 2023: 4; 2024: 5; 2025: 5; 2026: 7.

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  1. 2022Understanding Transformer Memorization Recall Through Idiomscited by 62
  2. 2023Do GPTs Produce Less Literal Translations?cited by 30
  3. 2023Translate Meanings, Not Just Words: IdiomKB's Role in Optimizing Idiomatic Translation with Language Modelscited by 24
  4. 2024Improving LLM Abilities in Idiomatic Translationcited by 16
  5. 2021Potential Idiomatic Expression (PIE)-English: Corpus for Classes of Idiomscited by 15
  6. 2024Semantics of Multiword Expressions in Transformer-Based Models: A Surveycited by 9
  7. 2025Memorization or Reasoning? Exploring the Idiom Understanding of LLMscited by 7
  8. 2021IBERT: Idiom Cloze-style reading comprehension with Attentioncited by 4
  9. 2024Using large language models to estimate features of multi-word expressions: Concreteness, valence, arousalcited by 4
  10. 2025Isolating Culture Neurons in Multilingual Large Language Modelscited by 4
  11. 2023That was the last straw, we need more: Are Translation Systems Sensitive to Disambiguating Context?cited by 3
  12. 2025NLP Datasets for Idiom and Figurative Language Taskscited by 2
12 more
  1. 2025CLIX: Cross-Lingual Explanations of Idiomatic Expressionscited by 1
  2. 2025Evaluating the Impact of Verbal Multiword Expressions on Machine Translationcited by 1
  3. 2026A Parallel Cross-Lingual Benchmark for Multimodal Idiomaticity Understandingcited by 1
  4. 2026SinFoS: A Parallel Dataset for Translating Sinhala Figures of Speechcited by 1
  5. 2023IdEALS: Idiomatic Expressions for Advancement of Language Skillscited by 0
  6. 2024Figuratively Speaking: Authorship Attribution via Multi-Task Figurative Language Modelingcited by 0
  7. 2024Large Language Models for Persian leftrightarrow English Idiom Translationcited by 0
  8. 2026Span Modeling for Idiomaticity and Figurative Language Detection with Span Contrastive Losscited by 0
  9. 2026Exploring Concreteness Through a Figurative Lenscited by 0
  10. 2026SiNFluD: Creating and Evaluating Figurative Language Dataset for Sindhicited by 0
  11. 2026IdioLink: Retrieving Meaning Beyond Words Across Idiomatic and Literal Expressionscited by 0
  12. 2026G-IdiomAlign: A Gloss-Pivoted Benchmark for Cross-Lingual Idiom Alignmentcited by 0