Semantic Annotation of Named Rivers and its Application for the Prediction of Multiword-Term Bracketing

Abstract

The acquisition of knowledge is essential for specialized translation, hence the representation of specialized phraseology in terminological knowledge bases is part of this process. The aim of this study was thus two-fold. Firstly, it describes how the semantic annotation of predicate-argument structure of sentences mentioning named rivers can be addressed from the perspective of Frame-based Terminology. The results showed that this approach provides valuable insights into the knowledge structures underlying the usage of named rivers in specialized texts. Secondly, this study explores whether the bracketing of a three-component multiword term can be predicted from the semantic information encoded in the sentence where the ternary compound and a named river are used as arguments. The semantic annotations permitted construction of two machine-learning models capable of accurately predicting ternary-compound bracketing.