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Chapter 5. Evaluating a bracketing protocol for multiword terms

  • Pilar León-Araúz und Melania Cabezas-García
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Recent Advances in Multiword Units in Machine Translation and Translation Technology
Ein Kapitel aus dem Buch Recent Advances in Multiword Units in Machine Translation and Translation Technology

Abstract

Multiword terms (MWTs) are frequently used to encapsulate and convey meaning in scientific and technical texts. However, they can also make these texts difficult to understand because the relations between constituents are not transparent. When MWTs have more than two constituents, a dependency analysis (bracketing) is often necessary to facilitate their interpretation. NLP has proposed various models to automatize bracketing operations, but none has been entirely satisfactory. This paper presents a protocol that combines various models and applies it to a set of three-constituent MWTs in order to: (i) sort rules by their disambiguation potential, based on their likelihood of retrieving results from any corpus and their ability to solve bracketing; and (ii) ascertain the influence of corpus size and type in the results obtained.

Abstract

Multiword terms (MWTs) are frequently used to encapsulate and convey meaning in scientific and technical texts. However, they can also make these texts difficult to understand because the relations between constituents are not transparent. When MWTs have more than two constituents, a dependency analysis (bracketing) is often necessary to facilitate their interpretation. NLP has proposed various models to automatize bracketing operations, but none has been entirely satisfactory. This paper presents a protocol that combines various models and applies it to a set of three-constituent MWTs in order to: (i) sort rules by their disambiguation potential, based on their likelihood of retrieving results from any corpus and their ability to solve bracketing; and (ii) ascertain the influence of corpus size and type in the results obtained.

Kapitel in diesem Buch

  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.366.05leo

Kapitel in diesem Buch

  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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Heruntergeladen am 20.9.2025 von https://www.degruyterbrill.com/document/doi/10.1075/cilt.366.05leo/html?lang=de
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