# Overview for the Second Shared Task on Language Identification in Code-Switched Data

arXiv: https://arxiv.org/abs/1909.13016 · HTML: https://mlsanity.com/paper/1909.13016/

## Key facts

- Cited by 33 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Sep 2019.

## Built on by (most cited first, 30 of 33)

- [The Decades Progress on Code-Switching Research in NLP: A Systematic Survey on Trends and Challenges](https://mlsanity.com/paper/2212.09660/) (2022)
- [ALDi: Quantifying the Arabic Level of Dialectness of Text](https://mlsanity.com/paper/2310.13747/) (2023)
- [Can You Traducir This? Machine Translation for Code-Switched Input](https://mlsanity.com/paper/2105.04846/) (2021)
- [Language Variety Identification with True Labels](https://mlsanity.com/paper/2303.01490/) (2023)
- [Comparing Approaches to Dravidian Language Identification](https://mlsanity.com/paper/2103.05552/) (2021)
- [MaskLID: Code-Switching Language Identification through Iterative Masking](https://mlsanity.com/paper/2406.06263/) (2024)
- [CodeMixBench: Evaluating Code-Mixing Capabilities of LLMs Across 18 Languages](https://mlsanity.com/paper/2507.18791/) (2025)
- [CALCS 2021 Shared Task: Machine Translation for Code-Switched Data](https://mlsanity.com/paper/2202.09625/) (2022)
- [El Volumen Louder Por Favor: Code-switching in Task-oriented Semantic Parsing](https://mlsanity.com/paper/2101.10524/) (2021)
- [Quality Evaluation of the Low-Resource Synthetically Generated Code-Mixed Hinglish Text](https://mlsanity.com/paper/2108.01861/) (2021)
- [Code-Mixed Probes Show How Pre-Trained Models Generalise On Code-Switched Text](https://mlsanity.com/paper/2403.04872/) (2024)
- [COMI-LINGUA: Expert Annotated Large-Scale Dataset for Multitask NLP in Hindi-English Code-Mixing](https://mlsanity.com/paper/2503.21670/) (2025)
- [Detecting Unassimilated Borrowings in Spanish: An Annotated Corpus and Approaches to Modeling](https://mlsanity.com/paper/2203.16169/) (2022)
- [Switch Point biased Self-Training: Re-purposing Pretrained Models for Code-Switching](https://mlsanity.com/paper/2111.01231/) (2021)
- [Borrowing or Codeswitching? Annotating for Finer-Grained Distinctions in Language Mixing](https://mlsanity.com/paper/2206.04973/) (2022)
- [CST5: Data Augmentation for Code-Switched Semantic Parsing](https://mlsanity.com/paper/2211.07514/) (2022)
- [A Survey of Code-switched Arabic NLP: Progress, Challenges, and Future Directions](https://mlsanity.com/paper/2501.13419/) (2025)
- [Beyond Monolingual Assumptions: A Survey of Code-Switched NLP in the Era of Large Language Models across Modalities](https://mlsanity.com/paper/2510.07037/) (2025)
- [Overview of ADoBo 2021: Automatic Detection of Unassimilated Borrowings in the Spanish Press](https://mlsanity.com/paper/2110.15682/) (2021)
- [Estimating the Level of Dialectness Predicts Interannotator Agreement in Multi-dialect Arabic Datasets](https://mlsanity.com/paper/2405.11282/) (2024)
- [Language Identification for Austronesian Languages](https://mlsanity.com/paper/2206.04327/) (2022)
- [Code-Switched Language Identification is Harder Than You Think](https://mlsanity.com/paper/2402.01505/) (2024)
- [Conditioning LLMs to Generate Code-Switched Text](https://mlsanity.com/paper/2502.12924/) (2025)
- [Low-resource Machine Translation for Code-switched Kazakh-Russian Language Pair](https://mlsanity.com/paper/2503.20007/) (2025)
- [niksss at HinglishEval: Language-agnostic BERT-based Contextual Embeddings with Catboost for Quality Evaluation of the Low-Resource Synthetically Generated Code-Mixed Hinglish Text](https://mlsanity.com/paper/2206.08910/) (2022)
- [Post-hoc analysis of Arabic transformer models](https://mlsanity.com/paper/2210.09990/) (2022)
- [Automatic Identification of Motivation for Code-Switching in Speech Transcripts](https://mlsanity.com/paper/2212.08565/) (2022)
- [The Effect of Alignment Objectives on Code-Switching Translation](https://mlsanity.com/paper/2309.05044/) (2023)
- [Computational Approaches to Arabic-English Code-Switching](https://mlsanity.com/paper/2410.13318/) (2024)
- [Interpreting Arabic Transformer Models](https://mlsanity.com/paper/2201.07434/) (2022)

## Abstract (arXiv)

We present an overview of the second shared task on language identification in code-switched data. For the shared task, we had code-switched data from two different language pairs: Modern Standard Arabic-Dialectal Arabic (MSA-DA) and Spanish-English (SPA-ENG). We had a total of nine participating teams, with all teams submitting a system for SPA-ENG and four submitting for MSA-DA. Through evaluation, we found that once again language identification is more difficult for the language pair that is more closely related. We also found that this year's systems performed better overall than the systems from the previous shared task indicating overall progress in the state of the art for this task.