# BiST: A Gold Standard Bangla-English Bilingual Corpus for Sentence Structure and Tense Classification with Inter-Annotator Agreement

arXiv: https://arxiv.org/abs/2604.04708 · HTML: https://mlsanity.com/paper/2604.04708/

## Key facts

- Cited by 1 papers in the map (data through 7 Oct 2026).
- Builds on 13 of its 21 references that are in the map.
- First posted on arXiv 6 Apr 2026.

## Builds on (most cited first, 13 of 13)

- [From Matching to Generation: A Survey on Generative Information Retrieval](https://mlsanity.com/paper/2404.14851/) (2024)
- [Controllable Text Generation for Large Language Models: A Survey](https://mlsanity.com/paper/2408.12599/) (2024)
- [On Cross-Lingual Retrieval with Multilingual Text Encoders](https://mlsanity.com/paper/2112.11031/) (2021)
- [Do Text Simplification Systems Preserve Meaning? A Human Evaluation via Reading Comprehension](https://mlsanity.com/paper/2312.10126/) (2023)
- [BanglaBook: A Large-scale Bangla Dataset for Sentiment Analysis from Book Reviews](https://mlsanity.com/paper/2305.06595/) (2023)
- [Cross-Lingual Transfer Learning for Speech Translation](https://mlsanity.com/paper/2407.01130/) (2024)
- [BnSentMix: A Diverse Bengali-English Code-Mixed Dataset for Sentiment Analysis](https://mlsanity.com/paper/2408.08964/) (2024)
- [Training Bilingual LMs with Data Constraints in the Targeted Language](https://mlsanity.com/paper/2411.12986/) (2024)
- [A Structured Dataset of Disease-Symptom Associations to Improve Diagnostic Accuracy](https://mlsanity.com/paper/2506.13610/) (2025)
- [LLMCL-GEC: Advancing Grammatical Error Correction with LLM-Driven Curriculum Learning](https://mlsanity.com/paper/2412.12541/) (2024)
- [Bridging the Gap in Bangla Healthcare: Machine Learning Based Disease Prediction Using a Symptoms-Disease Dataset](https://mlsanity.com/paper/2601.12068/) (2026)
- [The Responsible Development of Automated Student Feedback with Generative AI](https://mlsanity.com/paper/2308.15334/) (2023)
- [StanceMoE: Mixture-of-Experts Architecture for Stance Detection](https://mlsanity.com/paper/2604.00878/) (2026)

## Built on by (most cited first, 1 of 1)

- [Bangla Sentence Function Classification: Corpus Development, Model Benchmarking, and Interpretability](https://mlsanity.com/paper/2609.13869/) (2026)

## Abstract (arXiv)

High-quality bilingual resources remain a critical bottleneck for advancing multilingual NLP in low-resource settings, particularly for Bangla. To mitigate this gap, we introduce BiST, a rigorously curated Bangla-English corpus for sentence-level grammatical classification, annotated across two fundamental dimensions: syntactic structure (Simple, Complex, Compound, Complex-Compound) and tense (Present, Past, Future). The corpus is compiled from open-licensed encyclopedic sources and naturally composed conversational text, followed by systematic preprocessing and automated language identification, resulting in 30,534 sentences, including 17,465 English and 13,069 Bangla instances. Annotation quality is ensured through a multi-stage framework with three independent annotators and dimension-wise Fleiss Kappa (kappa) agreement, yielding reliable and reproducible labels with kappa values of 0.82 and 0.88 for structural and temporal annotation, respectively. Statistical analyses demonstrate realistic structural and temporal distributions, while baseline evaluations show that dual-encoder architectures leveraging complementary language-specific representations consistently outperform strong multilingual encoders. Beyond benchmarking, BiST provides explicit linguistic supervision that supports grammatical modeling tasks, including controlled text generation, automated feedback generation, and cross-lingual representation learning. The corpus establishes a unified resource for bilingual grammatical modeling and facilitates linguistically grounded multilingual research.