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