Enhancing Ontology Translation Through Cross-Lingual Agreement

Abstract

Ontology serves as the foundation for the underlying representation of knowledge. In order to achieve the sharing of knowledge across languages, ontologies that are typically only represented in English must be translated into different languages. Building a domain-specific translation system is necessary for ontology due to the extremely specialized vocabulary and absence of contextual information. In this paper, we introduce cross-lingual agreement to alleviate the aforementioned issues. We propose a method for representing ontology labels that constructs agreement constraint objects by minimizing the distances between source and target sides. We also integrate with adversarial learning to reduce the difference between the ontology label and the hypothesis generated by the translation model during the fine-tuning. Finally, the agreement modeling strategy is incorporated into the decoding phase to guide the generation of translation candidates. Experiments on the four domains English-to-German ontology show that the proposed method achieves significant improvements over the baselines.