@inproceedings{choudhary-oriordan-2022-cross,
    title = "Cross-lingual Semantic Role Labelling with the {V}alpal database knowledge",
    author = "Choudhary, Chinmay  and
      O{'}Riordan, Colm",
    editor = "Agirre, Eneko  and
      Apidianaki, Marianna  and
      Vuli{\'c}, Ivan",
    booktitle = "Proceedings of Deep Learning Inside Out (DeeLIO 2022): The 3rd Workshop on Knowledge Extraction and Integration for Deep Learning Architectures",
    month = may,
    year = "2022",
    address = "Dublin, Ireland and Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/bulk-corrections-2025-11-25/2022.deelio-1.1/",
    doi = "10.18653/v1/2022.deelio-1.1",
    pages = "1--10",
    abstract = "Cross-lingual Transfer Learning typically involves training a model on a high-resource source language and applying it to a low-resource target language. In this work we introduce a lexical database called Valency Patterns Leipzig (ValPal) which provides the argument pattern information about various verb-forms in multiple languages including low-resource languages. We also provide a framework to integrate the ValPal database knowledge into the state-of-the-art LSTM based model for cross-lingual semantic role labelling. Experimental results show that integrating such knowledge resulted in am improvement in performance of the model on all the target languages on which it is evaluated."
}