README.md

---
license: cc-by-nc-sa-4.0
task_categories:
- idiom-detection
- text-classification
- translation
language:
- en
- es
pretty_name: IdioTS - Idiomatic Language Test Suite
size_categories:
- n<1K
---
# Dataset Card for IdioTS - Idiomatic Language Test Suite

This repository includes the dataset for idiom detection and translation proposed in our [paper](https://aclanthology.org/2024.figlang-1.5/).


The first version of this evaluation dataset was created as part of a Master's thesis in NLP 
under the title "Idiom detection and translation with conversational LLMs".
The dataset has been further curated and improved and is constantly revised by the author.


## Dataset Details

### Dataset Description

<!-- Provide a longer summary of what this dataset is. -->



- **Curated by:** Francesca De Luca Fornaciari
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** cc-by-nc-sa-4.0

### Dataset Sources [optional]

<!-- Provide the basic links for the dataset. -->

- **Repository:** https://github.com/fdelucaf/idioms-sentences-extractor
- **Paper [optional]:** https://aclanthology.org/2024.figlang-1.5/
- **Demo [optional]:** [More Information Needed]

## Uses

This dataset is designed for the assessment of conversational LLMs' capabilities to process figurative language, 
specifically idiomatic expressions at sentence level.

### Direct Use

This dataset can be used for the assessment of conversational LLMs on two tasks related with idiomatic language:

Task 1 (monolingual task): idiom detection in an English sentence.

Task 2 (cross-lingual task): sentence translation from English to Spanish.


### Out-of-Scope Use

This dataset is not meant to be used for tasks that differ from the ones specified in "Direct Use". 

## Dataset Structure
### Data Instances
```

```

### Data Fields

- `idiom_id` (str): Unique ID assigned to the idiomatic expression.
- `idiom` (str): Idiomatic expression.
- `sentence_id` (str): Unique ID assigned to the sentence.
- `sentence_has_idiom` (bool): True/False field indicating wether the original English sentence contains an idiom or not.
- `en` (str): Original English sentence.
- `es` (str): Spanish sentence (translation).

  
### Data Splits

The dataset contains a single split: `test`.

## Dataset Creation

### Curation Rationale

This evaluation dataset was designed and curated by human experts with advanced linguistic knowledge, specifically to assess the ability of 
LLMs to process figurative language at sentence level.
With the release of this dataset, we aim to provide a resource for evaluating the capabilities of conversational LLMs 
to handle the semantic meanings of multi-word expressions and to distinguish between literal 
and idiomatic meanings of a potentially idiomatic expression (PIE).


### Source Data

The sentence dataset is based on an original list of English idioms. This list was curated by the same author as the dataset. 
The original English idioms are partly derived from real interactions of the author with native English speakers
and partly extracted from the following websites:
[Amigos Ingleses](https://www.amigosingleses.com/), 
[The idioms](https://www.theidioms.com/), 
[EF English idioms](https://www.ef.com/wwen/english-resources/english-idioms/).


#### Data Collection and Processing

The original English sentences in the dataset were crafted by a group of native English speakers 
in the frame of a small-scale crowdsourcing on voluntary basis.

#### Who are the source data producers?

In order to ensure the quality of the generated sentences, the selected collaborators had to fulfil the following requirements:
- Native English speakers, predominantly of British origins.
- Demonstrated high linguistic proficiency attaining at least a C1 level.
- Language professional profile with a linguistic background (English teachers, linguists, translators, and NLP experts).

The task definition was kept as simple as possible. 
The collaborators were provided with a spreadsheet extracted from the previously compiled list of idioms 
(containing just the idiom and an empty cell for the sentence, without any additional context) 
and were simply instructed to select a few of them of their choice and to craft a sentences per chosen idiom. 
They were asked to produce sentences representative of natural, spontaneous language use by native English speakers, 
allowing for humorous, personal, or improvised content, provided it resonated authentically with their native speaker experience. 
An example idiom with its corresponding sentence was included as a model in the email body:

Idiom: "to have bigger fish to fry". 
Sentence: "I don't have time for your silly stories, I have bigger fish to fry: I have a job interview to prepare  for tomorrow!".


### Annotations [optional]

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#### Annotation process

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[More Information Needed]

#### Who are the annotators?

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[More Information Needed]

#### Personal and Sensitive Information

The dataset does not contain any kind of personal or sensitive information.


## Bias, Risks, and Limitations

A concerted effort was made to mitigate gender bias within our newly developed resource. 
Whenever possible, gender-specific terms were either eliminated or neutralised, a large number of sentences 
were reformulated adopting a gender neutral first person plural ("we"/"us"), second person singular or 
plural ("you"), or third person plural ("they"). Since the gender neutralisation is not always possible 
due to grammatical or syntactical constraints, meticulous attention was devoted to ensuring a representation 
of feminine and masculine gender terms as balanced as possible throughout the dataset.

No specific measures were taken to mitigate other types of bias that may be present in the data.

### Recommendations

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## Citation [optional]

<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->

**BibTeX:**



**APA:**

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## Glossary [optional]

<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->

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## More Information [optional]

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## Dataset Card Authors [optional]

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## Dataset Card Contact

[email protected]