# X-SRL: A Parallel Cross-Lingual Semantic Role Labeling Dataset

arXiv: https://arxiv.org/abs/2010.01998 · HTML: https://mlsanity.com/paper/2010.01998/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Oct 2020.

## Built on by (most cited first, 15 of 15)

- [State-of-the-art generalisation research in NLP: A taxonomy and review](https://mlsanity.com/paper/2210.03050/) (2022)
- [Frustratingly Easy Label Projection for Cross-lingual Transfer](https://mlsanity.com/paper/2211.15613/) (2022)
- [Translate & Fill: Improving Zero-Shot Multilingual Semantic Parsing with Synthetic Data](https://mlsanity.com/paper/2109.04319/) (2021)
- [Everything Is All It Takes: A Multipronged Strategy for Zero-Shot Cross-Lingual Information Extraction](https://mlsanity.com/paper/2109.06798/) (2021)
- [FRASIMED: a Clinical French Annotated Resource Produced through Crosslingual BERT-Based Annotation Projection](https://mlsanity.com/paper/2309.10770/) (2023)
- [A Hybrid Intelligence Method for Argument Mining](https://mlsanity.com/paper/2403.09713/) (2024)
- [MultiMUC: Multilingual Template Filling on MUC-4](https://mlsanity.com/paper/2401.16209/) (2024)
- [DAHRS: Divergence-Aware Hallucination-Remediated SRL Projection](https://mlsanity.com/paper/2407.09283/) (2024)
- [Multilingual Coreference Resolution in Multiparty Dialogue](https://mlsanity.com/paper/2208.01307/) (2022)
- [Effective QA-driven Annotation of Predicate-Argument Relations Across Languages](https://mlsanity.com/paper/2602.22865/) (2026)
- [Zero-shot Cross-lingual Conversational Semantic Role Labeling](https://mlsanity.com/paper/2204.04914/) (2022)
- [An Interdisciplinary Perspective on Evaluation and Experimental Design for Visual Text Analytics: Position Paper](https://mlsanity.com/paper/2209.11534/) (2022)
- [Exploring Non-Verbal Predicates in Semantic Role Labeling: Challenges and Opportunities](https://mlsanity.com/paper/2307.01870/) (2023)
- [MetaXCR: Reinforcement-Based Meta-Transfer Learning for Cross-Lingual Commonsense Reasoning](https://mlsanity.com/paper/2503.06531/) (2025)
- [Just Use XML: Revisiting Joint Translation and Label Projection](https://mlsanity.com/paper/2603.12021/) (2026)

## Abstract (arXiv)

Even though SRL is researched for many languages, major improvements have mostly been obtained for English, for which more resources are available. In fact, existing multilingual SRL datasets contain disparate annotation styles or come from different domains, hampering generalization in multilingual learning. In this work, we propose a method to automatically construct an SRL corpus that is parallel in four languages: English, French, German, Spanish, with unified predicate and role annotations that are fully comparable across languages. We apply high-quality machine translation to the English CoNLL-09 dataset and use multilingual BERT to project its high-quality annotations to the target languages. We include human-validated test sets that we use to measure the projection quality, and show that projection is denser and more precise than a strong baseline. Finally, we train different SOTA models on our novel corpus for mono- and multilingual SRL, showing that the multilingual annotations improve performance especially for the weaker languages.