Forthcoming: Multiword expressions in Natural Language Processing: Current trends and challenges

Voula Giouli (ed), Verginica Barbu Mititelu (ed)

Synopsis

The present volume addresses the way in which multiword expression resources are used in real-life downstream Natural Language Processing applications, how they interact with neural architectures and generative pre-trained language models and, more broadly, how linguistic theory and computational modeling can inform each other. It critically examines the properties of multiword expression resources and their integration into – or exclusion from – contemporary Natural Language Processing systems dominated by machine learning and Large Language Models.

Chapters

  • Multiword expressions lexica for Natural Language Processing
    A state-of-the-art survey
    Voula Giouli, Verginica Barbu Mititelu, Stella Markantonatou, Ivelina Stoyanova, Alexandra Markovic, Irina Lobzhanidze, Rusudan Makhachashvili, Gražina Korvel, Chaya Liebeskind
  • Not as clear as black and white
    Exploring the potential usability of general language dictionaries in identifying multiword expressions
    Anna Vacalopoulou
  • Using multiword expression lexica in Natural Language Processing tasks
    A survey
    Voula Giouli, Verginica Barbu Mititelu, Irina Lobzhanidze, Gražina Korvel, Raquel Amaro, Svetla Koeva, Giedre Valunaite Oleskeviciene
  • Verbal idioms of European Portuguese
    An annotated corpus
    David Antunes, Eugénio Ribeiro, Jorge Baptista, Nuno Mamede
  • Effective multiword acquisition and applications in the SPECIALIST lexicon and lexical tools
    Chris Lu, Amanda Payne, James Mork
  • Identification and annotation of multiword expressions in an end-user application
    The case of teaching/learning French as a foreign language
    Agnieszka Dryjańska, Till Überrück-Fries, Agata Savary
  • Prompting Large Language Models for Multiword Expression recognition
    Vasile Păiș, Maria Mitrofan
  • Dancing with deer
    A constructional perspective on multiword expressions in the era of Large Language Models
    Claire Bonial, Harish Tayyar Madabushi, Julia Bonn
  • Fine-tuning BERT for masked language modelling and identification of sentences with verbal multiword expressions in the Modern Greek language
    Aggeliki Fotopoulou, Panagiota Kyriazi, Stavros Nousias

Biographies

Voula Giouli

Voula Giouli is an assistant professor at Aristotle University of Thessaloniki, Greece. She holds a MSc in Speech and Language Processing from the University of Edinburgh, and a PhD in Computational Linguistics from the University of Athens. She has been involved in the development of downstream Natural Language Processing resources (annotated corpora, computational lexica) and tools for the Greek language mainly in the area of Information Extraction, Machine Translation, Sentiment Analysis, and Digital Humanities. Her research focuses on the lexicon, syntax, semantics and their interfaces.

Verginica Barbu Mititelu

Verginica Barbu Mititelu is a senior researcher in the Natural Language Processing group of the Romanian Academy Research Institute for Artificial Intelligence. She performed her Master studies at and received her PhD in Philology in 2010 from the University of Bucharest. She has constantly been preoccupied with and involved in the development of language resources, especially for Romanian, applying up-to-date annotation schemas and adjusting them to the characteristics of the language under study. She has also been concerned with standardizing the resources developed, especially using Linked Data principles of representation, and with the registration of their metadata in international data repositories.

Book cover

Published

November 7, 2025
LaTeX source on GitHub

Print ISSN

2625-3127
Cite as
Giouli, Voula & Barbu Mititelu, Verginica (eds.). Forthcoming. Multiword expressions in Natural Language Processing: Current trends and challenges. (Phraseology and Multiword Expressions 8). Berlin: Language Science Press. DOI: 10.5281/zenodo.21276755

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Details about the available publication format: PDF

PDF

ISBN-13 (15)

978-3-96110-591-5

doi

10.5281/zenodo.21276755

Details about the available publication format: Hardcover

Hardcover

ISBN-13 (15)

978-3-98554-208-6

Physical Dimensions

180mm x 245mm