Frequent Semantically Non-Compositional Multiword Expressions in the English Subtitles of Military and War Films and Dramas

A Corpus-Based Study

Authors

  • Wenhua Hsu I-Shou University, Taiwan

DOI:

https://doi.org/10.33541/jet.v12i3.8740

Keywords:

multiword expressions, semantic non-compositionality, English subtitles, military films and dramas

Abstract

The expansion of over-the-top (OTT) streaming has popularized binge-watching television dramas. This study explores the potential for English lexical development among Taiwanese EFL college students who switch from Mandarin to English subtitles, focusing on military and war dramas as a source of extensive language exposure. Because military English features technical terms and semantically non-compositional multiword expressions (MWEs) that are underrepresented in general EFL materials, even proficient learners often struggle to comprehend military-themed audiovisual content. To address this gap, this study compiled a 60-million-word corpus from the English subtitles of 100 military drama series and 100 films. Using six selection criteria, the study identified 515 opaque MWEs of two to six words. To ensure the validity of the selected MWEs, human judgment was combined with corpus-based tools and Gemini Notebook for AI-assisted qualitative analysis. Most of these expressions consist of words from the 3,000 most frequent English word families, providing a practical, self-directed learning resource to improve comprehension of military-themed media.

References

Anthony, L. (2026a). AntConc (Version 4.4.2) [Computer software]. Waseda University. https://www.laurenceanthony.net/software/antconc/

Anthony, L. (2026b). AntWordProfiler (Version 2.3.0) [Computer software]. Waseda University. https://www.laurenceanthony.net/software/antwordprofiler/

Carver, R. P. (1994). Percentage of unknown words in text as a function of the relative difficulty of the text: Implications for instruction. Journal of Reading Behavior, 26, 413–437. https://doi.org/10.1080/10862969409547861

Georgieva, V., & Marinov, P. (2017). Intercultural interactions in a military context. Land Forces Academy Review, 22(3), 153-162. https://doi.org/10.1515/raft-2017-0021

Hinkel, E. (2023). Teaching and learning multiword expressions. In E. Hinkel (Ed.), Handbook of practical second language teaching and learning (pp. 435–448). Routledge. https://doi.org/10.4324/9781003106609-36

Hirsh, D., & Nation, I. S. P. (1992). What vocabulary size is needed to read unsimplified texts for pleasure? Reading in a Foreign Language, 8(2), 689–696.

http://hdl.handle.net/10125/67046

Horst, J. S. (2013). Context and repetition in word learning. Frontiers in Psychology, 4, Article 149. https://doi.org/10.3389/fpsyg.2013.00149

Horst, J. S., Parsons, K. L., & Bryan, N. M. (2011). Get the story straight: Contextual repetition promotes word learning from storybooks. Frontiers in Psychology, 2, Article 17. https://doi.org/10.3389/fpsyg.2011.00017

Hsu, W. (2023). Korean drama fever—Expanding English lexicon through watching English-subtitled K-dramas: The case of non-compositional multi-word expressions. Journal of English Teaching, 9(2), 269–285. https://doi.org/10.33541/jet.v9i2.4761

Hu, M., & Nation, I. S. P. (2000). Unknown vocabulary density and reading comprehension. Reading in a Foreign Language, 13(1), 403–430. http://hdl.handle.net/10125/66973

Hunston, S. (2002). Corpora in applied linguistics. Cambridge University Press.

https://doi.org/10.1017/CBO9781139524773

Hyland, K. (2008). As can be seen: Lexical bundles and disciplinary variation. English for Specific Purposes, 27(1), 4–21. https://doi.org/10.1016/j.esp.2007.06.001

Labrador, B. (2026). Capitalizing on genre-based corpora with the use of the AI-powered research tool Notebook LM. Alfinge. Revista de Filología, 37, 51–75.

https://doi.org/10.21071/arf.v37i.18449

Locher, M. A., & Messerli, T. C. (2020). Translating the other: Communal TV watching of Korean TV drama. Journal of Pragmatics, 170, 20–36.

https://doi.org/10.1016/j.pragma.2020.07.002

Martinez, R., & Murphy, V. A. (2011). Effect of frequency and idiomaticity on second language reading comprehension. TESOL Quarterly, 45(2), 267–290.

https://doi.org/10.5054/tq.2011.247708

Martinez, R., & Schmitt, N. (2012). A phrasal expressions list. Applied Linguistics, 33(3), 299–320. https://doi.org/10.1093/applin/ams010

Nation, I. S. P. (2006). How large a vocabulary is needed for reading and listening? The Canadian Modern Language Review, 63(1), 59–82. https://doi.org/10.3138/cmlr.63.1.59

Nation, I. S. P. (2014). How much input do you need to learn the most frequent 9,000 words? Reading in a Foreign Language, 26(2), 1–16. http://hdl.handle.net/10125/66881

Nation, I. S. P. (2017). The BNC/COCA level 6 word family lists (Version 1.0.0) [Data file]. http://www.victoria.ac.nz/lals/staff/paul-nation.aspx

Pedersen, J. (2019). Fansubbing in subtitling land: An investigation into the nature of fansubs in Sweden. Target, 31(1), 50–76. https://doi.org/10.1075/target.18017.ped

Rodgers, M. P. H., & Webb, S. (2011). Narrow viewing: The vocabulary in related television programs. TESOL Quarterly, 45(4), 689–717. https://doi.org/10.5054/tq.2011.268062

Rubenking, B., & Bracken, C. C. (2021). Binge watching and serial viewing: Comparing new media viewing habits in 2015 and 2020. Addictive Behaviors Reports, 14, Article 100356. https://doi.org/10.1016/j.abrep.2021.100356

Schmitt, N., Jiang, X., & Grabe, W. (2011). The percentage of words known in a text and reading comprehension. The Modern Language Journal, 95(1), 26–43.

https://doi.org/10.1111/j.1540-4781.2011.01146.x

Shin, D., & Nation, P. (2008). Beyond single words: The most frequent collocations in spoken English. ELT Journal, 62(4), 339–348. https://doi.org/10.1093/elt/ccm091

Simpson-Vlach, R., & Ellis, N. C. (2010). An academic formulas list: New methods in phraseology research. Applied Linguistics, 31(4), 487–512.

https://doi.org/10.1093/applin/amp058

Talaván Zanón, N. (2006). Using subtitles to enhance foreign language learning. Porta Linguarum, 6, 41–52. https://doi.org/10.30827/Digibug.30659

U.S. Department of War. (2025). The War Department unleashes AI on new GenAI.mil platform. https://www.war.gov/News/Releases/Release/Article/4354916/the-war-department-unleashes-ai-on-new-genaimil-platform/

Vasankari, L., & Koski, A. (2025). GenAI in the military: Trends and opportunities. Scandinavian Journal of Military Studies, 8(1), 416–434.

https://doi.org/10.31374/sjms.415

Webb, S., & Rodgers, M. P. H. (2009a). Vocabulary demands of television programs. Language Learning, 59(2), 335–366. https://doi.org/10.1111/j.1467-9922.2009.00509.x

Webb, S., & Rodgers, M. P. H. (2009b). The lexical coverage of movies. Applied Linguistics, 30(3), 407–427. https://doi.org/10.1093/applin/amp010

Wood, D. (2020). Classifying and identifying formulaic language. In S. Webb (Ed.), Routledge handbook of vocabulary studies (pp. 30–45). Routledge.

https://doi.org/10.4324/9780429291586-3

Downloads

Published

2026-10-29

Issue

Vol. 12 No. 3 (2026): Journal of English Teaching

Section

Articles

License

Copyright (c) 2026 JET (Journal of English Teaching)

Creative Commons License

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

Copyrights for articles published in JET are retained by the authors, with first publication rights granted to the journal. The journal/publisher is not responsible for subsequent uses of the work. It is the author's responsibility to bring an infringement action if so desired by the author.