InVeRo-XL: Making Cross-Lingual Semantic Role Labeling Accessible with Intelligible Verbs and Roles
Simone Conia, Riccardo Orlando, Fabrizio Brignone, Francesco Cecconi, Roberto Navigli
Abstract
Notwithstanding the growing interest in cross-lingual techniques for Natural Language Processing, there has been a surprisingly small number of efforts aimed at the development of easy-to-use tools for cross-lingual Semantic Role Labeling. In this paper, we fill this gap and present InVeRo-XL, an off-the-shelf state-of-the-art system capable of annotating text with predicate sense and semantic role labels from 7 predicate-argument structure inventories in more than 40 languages. We hope that our system – with its easy-to-use RESTful API and Web interface – will become a valuable tool for the research community, encouraging the integration of sentence-level semantics into cross-lingual downstream tasks. InVeRo-XL is available online at http://nlp.uniroma1.it/invero.- Anthology ID:
- 2021.emnlp-demo.36
- Volume:
- Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
- Month:
- November
- Year:
- 2021
- Address:
- Online and Punta Cana, Dominican Republic
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 319–328
- Language:
- URL:
- https://aclanthology.org/2021.emnlp-demo.36
- DOI:
- 10.18653/v1/2021.emnlp-demo.36
- Cite (ACL):
- Simone Conia, Riccardo Orlando, Fabrizio Brignone, Francesco Cecconi, and Roberto Navigli. 2021. InVeRo-XL: Making Cross-Lingual Semantic Role Labeling Accessible with Intelligible Verbs and Roles. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 319–328, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.
- Cite (Informal):
- InVeRo-XL: Making Cross-Lingual Semantic Role Labeling Accessible with Intelligible Verbs and Roles (Conia et al., EMNLP 2021)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2021.emnlp-demo.36.pdf