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Chapter 10. Semantic annotation of named rivers and its application for the prediction of multiword-term bracketing

  • Juan Rojas Garcia
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Recent Advances in Multiword Units in Machine Translation and Translation Technology
This chapter is in the book Recent Advances in Multiword Units in Machine Translation and Translation Technology

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 multi-word 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.

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 multi-word 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.

Chapters in this book

  1. Prelim pages i
  2. Table of contents v
  3. Preface vii
  4. Section 1. Computational treatment of multiword units
  5. Chapter 1. Multi-word units in neural machine translation 2
  6. Chapter 2. ReGap 18
  7. Chapter 3. Evaluating the Italian-English machine translation quality of MWUs in the domain of archaeology 40
  8. Chapter 4. Post-editing neural machine translation in specialised languages 57
  9. Chapter 5. Evaluating a bracketing protocol for multiword terms 79
  10. Section 2. Corpus-based and linguistic studies in phraseology
  11. Chapter 6. Suggestions for a new model of functional phraseme categorization for applied purposes 104
  12. Chapter 7. Verb collocations and their semantics in the specialized language of science 124
  13. Chapter 8. Negative–positive adjective pairing in travel journalism in English, Italian, and Polish 141
  14. Chapter 9. The middle construction and some machine translation issues 156
  15. Chapter 10. Semantic annotation of named rivers and its application for the prediction of multiword-term bracketing 173
  16. Chapter 11. Irony in American-English tweets 197
  17. Chapter 12. A comprehensive Japanese MWE lexicon 218
  18. Chapter 13. Ontology-based formalisation of Italian clitic verbal MWEs 243
  19. Index 263
https://doi.org/10.1075/cilt.366.10roj

Chapters in this book

  1. Prelim pages i
  2. Table of contents v
  3. Preface vii
  4. Section 1. Computational treatment of multiword units
  5. Chapter 1. Multi-word units in neural machine translation 2
  6. Chapter 2. ReGap 18
  7. Chapter 3. Evaluating the Italian-English machine translation quality of MWUs in the domain of archaeology 40
  8. Chapter 4. Post-editing neural machine translation in specialised languages 57
  9. Chapter 5. Evaluating a bracketing protocol for multiword terms 79
  10. Section 2. Corpus-based and linguistic studies in phraseology
  11. Chapter 6. Suggestions for a new model of functional phraseme categorization for applied purposes 104
  12. Chapter 7. Verb collocations and their semantics in the specialized language of science 124
  13. Chapter 8. Negative–positive adjective pairing in travel journalism in English, Italian, and Polish 141
  14. Chapter 9. The middle construction and some machine translation issues 156
  15. Chapter 10. Semantic annotation of named rivers and its application for the prediction of multiword-term bracketing 173
  16. Chapter 11. Irony in American-English tweets 197
  17. Chapter 12. A comprehensive Japanese MWE lexicon 218
  18. Chapter 13. Ontology-based formalisation of Italian clitic verbal MWEs 243
  19. Index 263
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