Multiword Units in Machine Translation and Translation Technology

Editors

Ruslan Mitkov | University of Wolverhampton

Johanna Monti | “L'Orientale” University of Naples

Gloria Corpas Pastor | University of Málaga

Violeta Seretan | University of Geneva

Hardbound – Available

ISBN 9789027200600 | EUR 99.00 | USD 149.00

e-Book –

ISBN 9789027264206 | EUR 99.00 | USD 149.00

The correct interpretation of Multiword Units (MWUs) is crucial to many applications in Natural Language Processing but is a challenging and complex task. In recent years, the computational treatment of MWUs has received considerable attention but there is much more to be done before we can claim that NLP and Machine Translation (MT) systems process MWUs successfully.
This volume provides a general overview of the field with particular reference to Machine Translation and Translation Technology and focuses on languages such as English, Basque, French, Romanian, German, Dutch and Croatian, among others. The chapters of the volume illustrate a variety of topics that address this challenge, such as the use of rule-based approaches, compound splitting techniques, MWU identification methodologies in multilingual applications, and MWU alignment issues.

[Current Issues in Linguistic Theory, 341] 2018. ix, 259 pp.

Publishing status: Available
Published online on 12 July 2018

https://doi.org/10.1075/cilt.341

Table of Contents

About the editors | pp. vii–x

Multiword units in machine translation and translation technology

Johanna Monti, Violeta Seretan, Gloria Corpas Pastor and Ruslan Mitkov | pp. 1–38

Part 1. Multiword units in machine translation

Analysing linguistic information about word combinations for a Spanish-Basque rule-based machine translation system

Uxoa Iñurrieta, Itziar Aduriz, Arantza Díaz Ilarraza, Gorka Labaka and Kepa Sarasola | pp. 39–60

How do students cope with machine translation output of multiword units? An exploratory study

Joke Daems, Michael Carl, Sonia Vandepitte, Robert Hartsuiker and Lieve Macken | pp. 61–80

Aligning verb + noun collocations to improve a French-Romanian FSMT system

Amalia Todirascu and Mirabela Navlea | pp. 81–100

Part 2. Multiword units in multilingual NLP applications

Multiword expressions in multilingual information extraction

Gregor Thurmair | pp. 101–124

A multilingual gold standard for translation spotting of German compounds and their corresponding multiword units in English, French, Italian and Spanish

Simon Clematide, Stéphanie Lehner, Johannes Graën and Martin Volk | pp. 125–146

Dutch compound splitting for bilingual terminology extraction

Lieve Macken and Arda Tezcan | pp. 147–162

Part 3. Identification and translation of multiword units

A flexible framework for collocation retrieval and translation from parallel and comparable corpora

Oscar Mendoza Rivera, Ruslan Mitkov and Gloria Corpas Pastor | pp. 163–180

On identification of bilingual lexical bundles for translation purposes: The case of an English-Polish comparable corpus of patient information leaflets

Łukasz Grabowski | pp. 181–200

The quest for croatian idioms as multiword units

Kristina Kocijan and Sara Librenjak | pp. 201–222

Corpus analysis of croatian constructions with the verb doći ‘to come’

Goranka Blagus Bartolec and Ivana Matas Ivanković | pp. 223–242

Anaphora resolution, collocations and translation

Eric Wehrli and Luka Nerima | pp. 243–256

Index

“[T]he book represents many interesting topics in the area of computational treatment of multiword expressions, with a special focus on MT and translation technology. [...] This book can essentially be viewed as an important contribution to a specialised area (i.e. computational treatment of MWUs) of interest, which will be a great help to NLP researchers, and MT researchers and users in particular.”

Rejwanul Haque, Andy Way, Dublin City University and Mohammed Hasanuzzaman, Cork Institute of Technology, Ireland, in Machine Translation Vol. 33 (2019)

“[T]he accuracy of MWU translations still remains a problem, and MWU processing and translation still pose the hardest challenges to MT and translation technology (TT). [...] [T]he book definitely makes an important contribution to MWU processing, thanks to the new angle it brings to the study of MWU in NLP and the diverse and innovative models for the computational treatment of MWU.”

Wang Hui and Zhang Xiaojun, Xi'an Jiaotong-Liverpool University, in Babel 65:5 (2019)

“The book covers the treatments of different types of MWUs (e.g. idioms, lexical bundles, collocations, compounds) in translation (i.e. by MT system or CAT software) and a number of use-cases. The first chapter by the editors of the book presents an extensive background study and survey on the computational treatment of MWUs in NLP applications (particularly with respect to different MT approaches).”

Rejwanul Haque, Dublin City University, Mohammed Hasanuzzaman, Cork Institute of Technology, and Andy Way, Dublin City University, in Machine Translation 33 (2021).

Cited by (11)

Cited by 11 other publications

Order by:

Corpas Pastor, Gloria & Laura Noriega-Santiáñez

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2024. Interpreter-mediated political communication N-Grammed: a corpus-driven discourse analysis of government interpreters’ (ideological) use of formulaic language. The Translator 30:4 ► pp. 571 ff.

Kübler, Natalie, Hanna Martikainen, Alexandra Mestivier & Mojca Pecman

2024. Post-editing neural machine translation in specialised languages. In Recent Advances in Multiword Units in Machine Translation and Translation Technology [Current Issues in Linguistic Theory, 366], ► pp. 57 ff.

Cabezas-García, Melania & Pilar León-Araúz

2023. Machine versus corpus-based translation of multiword terms. Digital Scholarship in the Humanities 38:Supplement_1 ► pp. i6 ff.

Lima Florido, Francisco Javier

2023. Computational and Corpus-Based Phraseology. TRANS: Revista de Traductología :27 ► pp. 289 ff.

Sánchez Rodas, Fernando

2023. Translation and interpreting of organisation names in the English and Spanish Eurolect: a corpus-based study. Romanica Olomucensia 35:1 ► pp. 157 ff.

Liu, Kanglong & Muhammad Afzaal

2021. Translator's Style Through Lexical Bundles: A Corpus-Driven Analysis of Two English Translations of Hongloumeng. Frontiers in Psychology 12

Haque, Rejwanul, Mohammed Hasanuzzaman & Andy Way

2019. Terminology Translation in Low-Resource Scenarios. Information 10:9 ► pp. 273 ff.

Monti, Johanna & Maria Pia di Buono

2019. PARSEME-It: an Italian corpus annotated with verbal multiword expressions. Italian Journal of Computational Linguistics 5:2 ► pp. 61 ff.

[no author supplied]

2023. Book reviews. Yearbook of Phraseology 14:1 ► pp. 225 ff.

This list is based on CrossRef data as of 2 january 2025. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.

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