2026
Bonenfant, Ahn; Caron, Peir-Olivier; Casademont, Anna Joan; Michaud, Myriam; Breton, Ariane; Mimeau, Catherine
Capturing syntactic learning in children: A novel test Miscellaneous
2026.
@misc{bonenfantCapturingSyntacticLearning2026,
title = {Capturing syntactic learning in children: A novel test},
author = {Ahn Bonenfant and Peir-Olivier Caron and Anna Joan Casademont and Myriam Michaud and Ariane Breton and Catherine Mimeau},
year = {2026},
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Marshman, Elizabeth; Liu, Ting; Alfetlawi, Anwar; Naji, Haifa Ben; Bedeir, Ahmed Elhuseiny; Hassan, Mohammed Gamal; Nessakh, Hana
ChatGPT for translation-friendly editing: Researchers’ friend or foe? Proceedings Article
In: Proceedings of Convergence 2026, Surrey, 2026.
@inproceedings{marshmanChatGPTTranslationfriendlyEditing2026,
title = {ChatGPT for translation-friendly editing: Researchers’ friend or foe?},
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Mimeau, Catherine; Bonenfant, Anh; Caron, Pier-Olivier; Casademont, Anna Joan; Michaud, Myriam; Breton, Ariane
Creating a Syntactic Learning Test for French-Speaking Children Journal Article
In: 2026.
@article{mimeauCreatingSyntacticLearning2026,
title = {Creating a Syntactic Learning Test for French-Speaking Children},
author = {Catherine Mimeau and Anh Bonenfant and Pier-Olivier Caron and Anna Joan Casademont and Myriam Michaud and Ariane Breton},
url = {https://osf.io/5q73d},
year = {2026},
date = {2026-05-01},
urldate = {2026-05-04},
publisher = {OSF},
abstract = {Syntax, or the rules that state how to organize words into sentences, is a core component of human language, often affected in developmental language disorder. The aim of this study is to develop a novel test to measure individual differences in syntactic learning among French-speaking children aged 5–8 years. While several standardized tests evaluate children’s existing knowledge of syntax, few directly capture the dynamic process through which new syntactic structures are learned. Because learning is the mechanism through which linguistic knowledge emerges, measuring syntactic learning may provide important insights into typical and atypical language development. The novel test exposes children to sentences composed of familiar French words ordered with a non-canonical subject–object–verb (SOV) structure. Sentences are presented in blocks of increasing structural complexity. The test is administered across two sessions separated by approximately one week and includes three subtests: (1) comprehension, (2) judgment and (3) production. Corrective feedback is provided after each trial to enable incremental learning. Accuracy and reaction time are recorded on each trial, allowing modeling of individual learning trajectories using mixed-effects models. We will test approximately 40 French-speaking children aged 5–8 years. We will examine whether group performance improves across trials, indicating that the test elicits measurable learning. We also expect to find substantial individual differences in children’s learning trajectories.},
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Syntax, or the rules that state how to organize words into sentences, is a core component of human language, often affected in developmental language disorder. The aim of this study is to develop a novel test to measure individual differences in syntactic learning among French-speaking children aged 5–8 years. While several standardized tests evaluate children’s existing knowledge of syntax, few directly capture the dynamic process through which new syntactic structures are learned. Because learning is the mechanism through which linguistic knowledge emerges, measuring syntactic learning may provide important insights into typical and atypical language development. The novel test exposes children to sentences composed of familiar French words ordered with a non-canonical subject–object–verb (SOV) structure. Sentences are presented in blocks of increasing structural complexity. The test is administered across two sessions separated by approximately one week and includes three subtests: (1) comprehension, (2) judgment and (3) production. Corrective feedback is provided after each trial to enable incremental learning. Accuracy and reaction time are recorded on each trial, allowing modeling of individual learning trajectories using mixed-effects models. We will test approximately 40 French-speaking children aged 5–8 years. We will examine whether group performance improves across trials, indicating that the test elicits measurable learning. We also expect to find substantial individual differences in children’s learning trajectories.
Bulté, Bram; Terryn, Ayla Rigouts
LLMs and Cultural Values: The Impact of Prompt Language and Explicit Cultural Framing Journal Article
In: Computational Linguistics, pp. 1–88, 2026, ISSN: 0891-2017.
@article{bulteLLMsCulturalValues2026,
title = {LLMs and Cultural Values: The Impact of Prompt Language and Explicit Cultural Framing},
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abstract = {Large language models (LLMs) are rapidly being adopted by users across the globe, who interact with them in a diverse range of languages. At the same time, there are well-documented imbalances in the training data and optimization objectives of this technology, raising doubts as to whether LLMs can accurately represent the cultural diversity of their broad user base. In this study, we look at LLMs and cultural values in particular, and examine how prompt language and cultural framing influence model responses and their alignment with human values in different countries. We do so by probing 10 LLMs with 63 items from the Hofstede Values Survey Module and World Values Survey, translated into 11 languages, and formulated as prompts with and without different explicit cultural perspectives.Our study confirms that both prompt language and cultural perspective produce variation in LLM outputs, but with an important caveat: While targeted prompting can, to a certain extent, steer LLM responses in the direction of the predominant values of the corresponding countries, it does not overcome the models’ systematic bias toward the values associated with a restricted set of countries in our dataset: the Netherlands, Germany, the United States, and Japan. All tested models, regardless of their origin, exhibit remarkably similar patterns: They produce fairly neutral responses on most topics, with selective progressive stances on issues such as social tolerance. Alignment with cultural values of human respondents is improved more with an explicit cultural perspective than with a targeted prompt language. Unexpectedly, combining both approaches is no more effective than cultural framing with an English prompt. These findings reveal that LLMs occupy an uncomfortable middle ground: They are responsive enough to changes in prompts to produce variation, but they are also too firmly anchored to specific cultural defaults to adequately represent cultural diversity.},
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Large language models (LLMs) are rapidly being adopted by users across the globe, who interact with them in a diverse range of languages. At the same time, there are well-documented imbalances in the training data and optimization objectives of this technology, raising doubts as to whether LLMs can accurately represent the cultural diversity of their broad user base. In this study, we look at LLMs and cultural values in particular, and examine how prompt language and cultural framing influence model responses and their alignment with human values in different countries. We do so by probing 10 LLMs with 63 items from the Hofstede Values Survey Module and World Values Survey, translated into 11 languages, and formulated as prompts with and without different explicit cultural perspectives.Our study confirms that both prompt language and cultural perspective produce variation in LLM outputs, but with an important caveat: While targeted prompting can, to a certain extent, steer LLM responses in the direction of the predominant values of the corresponding countries, it does not overcome the models’ systematic bias toward the values associated with a restricted set of countries in our dataset: the Netherlands, Germany, the United States, and Japan. All tested models, regardless of their origin, exhibit remarkably similar patterns: They produce fairly neutral responses on most topics, with selective progressive stances on issues such as social tolerance. Alignment with cultural values of human respondents is improved more with an explicit cultural perspective than with a targeted prompt language. Unexpectedly, combining both approaches is no more effective than cultural framing with an English prompt. These findings reveal that LLMs occupy an uncomfortable middle ground: They are responsive enough to changes in prompts to produce variation, but they are also too firmly anchored to specific cultural defaults to adequately represent cultural diversity.
John, Paul; Martín, Antonio San
Machine Translation for Language Learning Book Section
In: Chapelle, Carol A. (Ed.): The Encyclopedia of Applied Linguistics, pp. 1–7, Wiley, 2026, ISBN: 978-1-4051-9473-0 978-1-4051-9843-1.
@incollection{johnMachineTranslationLanguage2026,
title = {Machine Translation for Language Learning},
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abstract = {Abstract
When neural machine translation was integrated into Google Translate in 2016, higher‐quality machine translation (MT) became available to serve a range of purposes, including learning a second language (L2). Free online MT systems such as Google Translate and DeepL, while impressive in their capabilities, are nonetheless not infallible. MT performance is notably modulated by genre and by language pair, with closely related languages and high‐resource languages (for which extensive bilingual corpora exist) benefiting from greater accuracy. MT can also reproduce the gender, racial, or ethnic biases and stereotypes present in corpora. Insofar as language learners are aware of these limitations, ideally receiving training to address the issues, MT can be effectively leveraged for language acquisition. Incidental L2 learning is a potential byproduct of MT use for professional or personal communication, for example, in the workplace or for tourism. Intentional learning is more closely associated with formal classes or with autonomous, self‐directed learners. MT can be accessed for L2 compositions, with learners comparing their own and MT formulations to promote noticing and metalinguistic awareness. MT can also be used in activities that target specific L2 features appropriate to learners' age and proficiency. Unfortunately, MT use at times complicates formative and summative assessment, making it hard to identify learner needs and achievements. Nonetheless, the many features of online MT (e.g., dictionary, spellchecker, and text‐to‐speech and speech recognition functionalities) make it an invaluable, multifaceted resource for independent and classroom‐based L2 learning.},
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Abstract
When neural machine translation was integrated into Google Translate in 2016, higher‐quality machine translation (MT) became available to serve a range of purposes, including learning a second language (L2). Free online MT systems such as Google Translate and DeepL, while impressive in their capabilities, are nonetheless not infallible. MT performance is notably modulated by genre and by language pair, with closely related languages and high‐resource languages (for which extensive bilingual corpora exist) benefiting from greater accuracy. MT can also reproduce the gender, racial, or ethnic biases and stereotypes present in corpora. Insofar as language learners are aware of these limitations, ideally receiving training to address the issues, MT can be effectively leveraged for language acquisition. Incidental L2 learning is a potential byproduct of MT use for professional or personal communication, for example, in the workplace or for tourism. Intentional learning is more closely associated with formal classes or with autonomous, self‐directed learners. MT can be accessed for L2 compositions, with learners comparing their own and MT formulations to promote noticing and metalinguistic awareness. MT can also be used in activities that target specific L2 features appropriate to learners' age and proficiency. Unfortunately, MT use at times complicates formative and summative assessment, making it hard to identify learner needs and achievements. Nonetheless, the many features of online MT (e.g., dictionary, spellchecker, and text‐to‐speech and speech recognition functionalities) make it an invaluable, multifaceted resource for independent and classroom‐based L2 learning.
When neural machine translation was integrated into Google Translate in 2016, higher‐quality machine translation (MT) became available to serve a range of purposes, including learning a second language (L2). Free online MT systems such as Google Translate and DeepL, while impressive in their capabilities, are nonetheless not infallible. MT performance is notably modulated by genre and by language pair, with closely related languages and high‐resource languages (for which extensive bilingual corpora exist) benefiting from greater accuracy. MT can also reproduce the gender, racial, or ethnic biases and stereotypes present in corpora. Insofar as language learners are aware of these limitations, ideally receiving training to address the issues, MT can be effectively leveraged for language acquisition. Incidental L2 learning is a potential byproduct of MT use for professional or personal communication, for example, in the workplace or for tourism. Intentional learning is more closely associated with formal classes or with autonomous, self‐directed learners. MT can be accessed for L2 compositions, with learners comparing their own and MT formulations to promote noticing and metalinguistic awareness. MT can also be used in activities that target specific L2 features appropriate to learners' age and proficiency. Unfortunately, MT use at times complicates formative and summative assessment, making it hard to identify learner needs and achievements. Nonetheless, the many features of online MT (e.g., dictionary, spellchecker, and text‐to‐speech and speech recognition functionalities) make it an invaluable, multifaceted resource for independent and classroom‐based L2 learning.
Jourdain, Isabelle; Mestokosho, Sabine; St-Gelais, Myriam; Thernish, Anne-Christina
L’Institut Tshakapesh : valoriser l’innu-aimun et projet Uauitamutau assi (Parlons du territoire !) Miscellaneous
2026.
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title = {L’Institut Tshakapesh : valoriser l’innu-aimun et projet Uauitamutau assi (Parlons du territoire !)},
author = {Isabelle Jourdain and Sabine Mestokosho and Myriam St-Gelais and Anne-Christina Thernish},
url = {https://rali.iro.umontreal.ca/rali/?q=fr/node/1222/show/3980},
year = {2026},
date = {2026-03-01},
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abstract = {Cette présentation comportera deux volets. D'abord, elle donnera un aperçu des moyens qu'a l’Institut Tshakapesh pour mettre de l’avant la richesse de la langue innue et l’importance des savoirs traditionnels. De plus, un projet de recherche au cœur du territoire sera présenté.
Le second volet portera sur les premières étapes d’un projet intitulé Uauitamutau assi (Parlons du territoire, parlons de l’environnement) : terminologie de l’environnement en langue innue. Le projet, fruit d'une collaboration entre l’Université de Montréal, cinq transcriptrices de langue maternelle innue et l’Institut Tshakapesh à Uashat mak Mani-utenam (Sept-Îles), a pour but de recueillir et de documenter le lexique environnemental spécifique à cette langue. Il sera question, notamment, du corpus sélectionné à partir d’enregistrements vidéo de récits oraux en langue innue disponibles sur le site de l’Institut Tshakapesh, de la transcription de ces histoires orales et de certains défis soulevés par la transcription des histoires orales.},
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Cette présentation comportera deux volets. D'abord, elle donnera un aperçu des moyens qu'a l’Institut Tshakapesh pour mettre de l’avant la richesse de la langue innue et l’importance des savoirs traditionnels. De plus, un projet de recherche au cœur du territoire sera présenté.
Le second volet portera sur les premières étapes d’un projet intitulé Uauitamutau assi (Parlons du territoire, parlons de l’environnement) : terminologie de l’environnement en langue innue. Le projet, fruit d'une collaboration entre l’Université de Montréal, cinq transcriptrices de langue maternelle innue et l’Institut Tshakapesh à Uashat mak Mani-utenam (Sept-Îles), a pour but de recueillir et de documenter le lexique environnemental spécifique à cette langue. Il sera question, notamment, du corpus sélectionné à partir d’enregistrements vidéo de récits oraux en langue innue disponibles sur le site de l’Institut Tshakapesh, de la transcription de ces histoires orales et de certains défis soulevés par la transcription des histoires orales.
Le second volet portera sur les premières étapes d’un projet intitulé Uauitamutau assi (Parlons du territoire, parlons de l’environnement) : terminologie de l’environnement en langue innue. Le projet, fruit d'une collaboration entre l’Université de Montréal, cinq transcriptrices de langue maternelle innue et l’Institut Tshakapesh à Uashat mak Mani-utenam (Sept-Îles), a pour but de recueillir et de documenter le lexique environnemental spécifique à cette langue. Il sera question, notamment, du corpus sélectionné à partir d’enregistrements vidéo de récits oraux en langue innue disponibles sur le site de l’Institut Tshakapesh, de la transcription de ces histoires orales et de certains défis soulevés par la transcription des histoires orales.
L'Homme, Marie-Claude
Transcription des histoires orales, protocole et logiciel de sous-titrage Miscellaneous
2026.
@misc{lhommeTranscriptionHistoiresOrales2026,
title = {Transcription des histoires orales, protocole et logiciel de sous-titrage},
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Casademont, Anna Joan; Gagné, Nancy
In: Palacios-Rodríguez, Antonio; Mejía, Radhames; Marrero-Sera, Eloísa; Cruz-Pichardo, Ivanovnna (Ed.): Innovación Educativa e Inclusión Digital: Fundamentos, Prácticas y Perspectivas Contemporáneas, pp. 75–90, Dykinson, Madrid, Espagne, 2026, ISBN: 979-13-7047-139-2.
@incollection{joancasademontCatalanComoLengua2026,
title = {El catalán como lengua adicional: análisis de corpus, propuestas pedagógicas con validez ecológica y emancipación digital del profesorado},
author = {Anna Joan Casademont and Nancy Gagné},
editor = {Antonio Palacios-Rodríguez and Radhames Mejía and Eloísa Marrero-Sera and Ivanovnna Cruz-Pichardo},
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Bach, Carme; Casademont, Anna Joan
In: Estudis Romànics, vol. 48, pp. 23–45, 2026.
@article{bachInfluenciesInterlinguistiquesEls2026,
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author = {Carme Bach and Anna Joan Casademont},
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Terryn, Ayla Rigouts
Large Language Models Are Good Term Extractors: A Systematic Evaluation Proceedings Article
In: Proceedings of the Fifteenth Language Resources and Evaluation Conference (LREC 2026), pp. 7631–7643, European Language Resources Association (ELRA), 2026.
@inproceedings{rigoutsterrynLargeLanguageModels2026,
title = {Large Language Models Are Good Term Extractors: A Systematic Evaluation},
author = {Ayla Rigouts Terryn},
doi = {10.63317/49gta5itne3q},
year = {2026},
date = {2026-01-01},
booktitle = {Proceedings of the Fifteenth Language Resources and Evaluation Conference (LREC 2026)},
pages = {7631–7643},
publisher = {European Language Resources Association (ELRA)},
abstract = {This paper systematically evaluates modern large language models for automatic term extraction (ATE), examining GPT-5 and Mistral across four domains and three languages using the ACTER corpus. The study compares model sizes, evaluates reasoning-enhanced variants, and tests prompting strategies aligned with human annotation guidelines. Beyond extracting term lists, models provide term labels, confidence scores, and terminology management remarks. Current large language models achieve F1 scores of .36-.72; while seemingly low, this is competitive with supervised approaches and approaches the human inter-annotator agreement ceiling of 0.59. Larger models outperform smaller variants, with reasoning-enhanced models showing modest improvements. Qualitative error analysis reveals that evaluation methodology partly misrepresents model capabilities: many extractions classified as errors represent defensible boundary judgements, and apparent hallucinations are predominantly (though not exclusively) valid normalisations. Limitations remain in fine-grained categorisation and handling overly general expressions. However, the convergence of model scores with each other and with human inter-annotator agreement suggests that, for high-resource languages, basic ATE may no longer be the bottleneck in terminology management pipelines, and research should shift toward downstream tasks such as definition generation and ontology construction.},
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This paper systematically evaluates modern large language models for automatic term extraction (ATE), examining GPT-5 and Mistral across four domains and three languages using the ACTER corpus. The study compares model sizes, evaluates reasoning-enhanced variants, and tests prompting strategies aligned with human annotation guidelines. Beyond extracting term lists, models provide term labels, confidence scores, and terminology management remarks. Current large language models achieve F1 scores of .36-.72; while seemingly low, this is competitive with supervised approaches and approaches the human inter-annotator agreement ceiling of 0.59. Larger models outperform smaller variants, with reasoning-enhanced models showing modest improvements. Qualitative error analysis reveals that evaluation methodology partly misrepresents model capabilities: many extractions classified as errors represent defensible boundary judgements, and apparent hallucinations are predominantly (though not exclusively) valid normalisations. Limitations remain in fine-grained categorisation and handling overly general expressions. However, the convergence of model scores with each other and with human inter-annotator agreement suggests that, for high-resource languages, basic ATE may no longer be the bottleneck in terminology management pipelines, and research should shift toward downstream tasks such as definition generation and ontology construction.
L'Homme, Marie-Claude; Mollen, Yvette; St-Gelais, Myriam
Le projet Uauitamutau assi. Terminologie de l’environnement en langue innue (innu-aimun) Journal Article
In: Littoral. La revue des écrits nord-côtiers, no. 20, pp. 96–101, 2026, ISSN: 1911-5237.
@article{lhommeProjetUauitamutauAssi2026,
title = {Le projet Uauitamutau assi. Terminologie de l’environnement en langue innue (innu-aimun)},
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abstract = {Le projet «"Uauitamutau assi. Terminologie de l’environnement en langue innue (innu-aimun)"»"est né du
désir d’un travail collaboratif entre Marie-Claude L’Homme et Yvette Mollen, toutes deux professeures au Département de linguistique et traduction de l’Université de Montréal. En effet, lors de la nomination de Yvette Mollen comme professeure agrégée en juin 2022, Marie-Claude L’Homme a immédiatement manifesté son intérêt auprès d’elle a!n de développer un projet qui mettrait à pro!t leurs deux expertises, soit celles de la terminologie et celle de la langue innue. Marie-Claude L’Homme, ayant déjà travaillé sur la terminologie environnementale dans diverses langues, a proposé à Yvette Mollen de travailler sur la terminologie environnementale en langue innue. En discutant, les deux collègues ont rapidement constaté qu’il serait nécessaire d’adapter la méthodologie de travail à la langue innue a!n de prendre en compte les savoirs spéci!ques aux communautés innues et la collecte des termes dans une langue où peu de documentation spécialisée est
immédiatement accessible. En effet, comme l’explique Yvette Mollen, locutrice native de la langue innue, les
concepts environnementaux en langue innue sont ancrés dans des savoirs millénaires en lien avec le mode de
vie ancestral des Innus. Leur traduction, leur compréhension et leur transmission nécessitent donc de prendre en compte ces savoirs dans ce domaine1.},
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Le projet «"Uauitamutau assi. Terminologie de l’environnement en langue innue (innu-aimun)"»"est né du
désir d’un travail collaboratif entre Marie-Claude L’Homme et Yvette Mollen, toutes deux professeures au Département de linguistique et traduction de l’Université de Montréal. En effet, lors de la nomination de Yvette Mollen comme professeure agrégée en juin 2022, Marie-Claude L’Homme a immédiatement manifesté son intérêt auprès d’elle a!n de développer un projet qui mettrait à pro!t leurs deux expertises, soit celles de la terminologie et celle de la langue innue. Marie-Claude L’Homme, ayant déjà travaillé sur la terminologie environnementale dans diverses langues, a proposé à Yvette Mollen de travailler sur la terminologie environnementale en langue innue. En discutant, les deux collègues ont rapidement constaté qu’il serait nécessaire d’adapter la méthodologie de travail à la langue innue a!n de prendre en compte les savoirs spéci!ques aux communautés innues et la collecte des termes dans une langue où peu de documentation spécialisée est
immédiatement accessible. En effet, comme l’explique Yvette Mollen, locutrice native de la langue innue, les
concepts environnementaux en langue innue sont ancrés dans des savoirs millénaires en lien avec le mode de
vie ancestral des Innus. Leur traduction, leur compréhension et leur transmission nécessitent donc de prendre en compte ces savoirs dans ce domaine1.
désir d’un travail collaboratif entre Marie-Claude L’Homme et Yvette Mollen, toutes deux professeures au Département de linguistique et traduction de l’Université de Montréal. En effet, lors de la nomination de Yvette Mollen comme professeure agrégée en juin 2022, Marie-Claude L’Homme a immédiatement manifesté son intérêt auprès d’elle a!n de développer un projet qui mettrait à pro!t leurs deux expertises, soit celles de la terminologie et celle de la langue innue. Marie-Claude L’Homme, ayant déjà travaillé sur la terminologie environnementale dans diverses langues, a proposé à Yvette Mollen de travailler sur la terminologie environnementale en langue innue. En discutant, les deux collègues ont rapidement constaté qu’il serait nécessaire d’adapter la méthodologie de travail à la langue innue a!n de prendre en compte les savoirs spéci!ques aux communautés innues et la collecte des termes dans une langue où peu de documentation spécialisée est
immédiatement accessible. En effet, comme l’explique Yvette Mollen, locutrice native de la langue innue, les
concepts environnementaux en langue innue sont ancrés dans des savoirs millénaires en lien avec le mode de
vie ancestral des Innus. Leur traduction, leur compréhension et leur transmission nécessitent donc de prendre en compte ces savoirs dans ce domaine1.
Martín, Antonio San; Faber, Pamela; Sánchez-Cárdenas, Beatriz; Vezzani, Federica; Nunzio, Giorgio Di (Ed.)
New Directions in Digital Terminology Research Book
Brill, Leiden, 2026.
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Martín, Antonio San
Terminological Definitions in the Face of Generative Artificial Intelligence Book Section
In: New Directions in Digital Terminology Research, pp. 184–221, Brill, Leiden, 2026.
@incollection{sanmartinTerminologicalDefinitionsFace2026,
title = {Terminological Definitions in the Face of Generative Artificial Intelligence},
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year = {2026},
date = {2026-01-01},
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Martín, Antonio San; Faber, Pamela; Sánchez-Cárdenas, Beatriz; Vezzani, Federica; Nunzio, Giorgio Di
Introduction Book Section
In: New Directions in Digital Terminology Research, pp. 1–8, Brill, Leiden, 2026.
@incollection{sanmartinIntroduction2026,
title = {Introduction},
author = {Antonio San Martín and Pamela Faber and Beatriz Sánchez-Cárdenas and Federica Vezzani and Giorgio Di Nunzio},
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year = {2026},
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Martín, Antonio San
Toward Human-Centered AI-Assisted Terminology Work Journal Article
In: Terminology, 2026, (arXiv:2512.18859 [cs]).
@article{sanmartinHumanCenteredAIAssistedTerminology2025,
title = {Toward Human-Centered AI-Assisted Terminology Work},
author = {Antonio San Martín},
url = {http://arxiv.org/abs/2512.18859},
doi = {10.48550/arXiv.2512.18859},
year = {2026},
date = {2026-01-01},
urldate = {2026-01-31},
journal = {Terminology},
abstract = {The rapid diffusion of generative artificial intelligence is transforming terminology work. While this technology promises gains in efficiency, its unstructured adoption risks weakening professional autonomy, amplifying bias, and eroding linguistic and conceptual diversity. This paper argues that a human-centered approach to artificial intelligence has become a necessity for terminology work. Building on research in artificial intelligence and translation studies, it proposes a human-centered framework that conceptualizes artificial intelligence as a means of amplifying the terminologist's capabilities, rather than replacing them. The framework is organized around three interrelated dimensions: the augmented terminologist, ethical AI, and human-centered design. Together, these dimensions emphasize the compatibility of high automation with strong human control, the central role of terminologists in bias mitigation, and the importance of designing AI tools and workflows around the needs, values, and well-being of the terminologist. The paper concludes by stressing that current choices in AI adoption will shape not only terminological practice, but also the preservation of accuracy, adequacy, and diversity in terminology and specialized knowledge.},
note = {arXiv:2512.18859 [cs]},
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The rapid diffusion of generative artificial intelligence is transforming terminology work. While this technology promises gains in efficiency, its unstructured adoption risks weakening professional autonomy, amplifying bias, and eroding linguistic and conceptual diversity. This paper argues that a human-centered approach to artificial intelligence has become a necessity for terminology work. Building on research in artificial intelligence and translation studies, it proposes a human-centered framework that conceptualizes artificial intelligence as a means of amplifying the terminologist's capabilities, rather than replacing them. The framework is organized around three interrelated dimensions: the augmented terminologist, ethical AI, and human-centered design. Together, these dimensions emphasize the compatibility of high automation with strong human control, the central role of terminologists in bias mitigation, and the importance of designing AI tools and workflows around the needs, values, and well-being of the terminologist. The paper concludes by stressing that current choices in AI adoption will shape not only terminological practice, but also the preservation of accuracy, adequacy, and diversity in terminology and specialized knowledge.
2025
L'Homme, Marie-CLaude
Representation of Multiword Expressions in Terminology Resources: from a traditional to a construction-based approach Journal Article
In: Terminology, vol. online first, 2025, ISSN: 0929-9971.
@article{lhommeRepresentationMultiwordExpressions2025,
title = {Representation of Multiword Expressions in Terminology Resources: from a traditional to a construction-based approach},
author = {Marie-CLaude L'Homme},
url = {https://benjamins.com/catalog/term.25029.lho},
doi = {https://doi.org/10.1075/term.25029.lho},
issn = {0929-9971},
year = {2025},
date = {2025-12-01},
journal = {Terminology},
volume = {online first},
publisher = {John Benjamins},
abstract = {Multiword terms are units that terminologists deal with in their everyday work. In terminology, the relevance of multiword terms is argued on the basis that they label concepts in knowledge structures. However, the identification of multiword terms in texts, their specific features when compared to other multiword expressions, and their representation in terminology resources raise many questions. This article examines some problems related to the traditional recording in terminology resources which basically consists in creating separate entries for multiword terms. It then compares two alternative approaches: 1. a lexical approach that records different kinds of multiword expressions as subentries; and 2. a construction-based approach that captures sets of multiword expressions as patterns. The two methods are illustrated with environment terms. The comparison shows that the construction-based approach is very promising as that it can prevent some of the shortcomings of the other ones. A proposal for its implementation is presented.},
keywords = {},
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Multiword terms are units that terminologists deal with in their everyday work. In terminology, the relevance of multiword terms is argued on the basis that they label concepts in knowledge structures. However, the identification of multiword terms in texts, their specific features when compared to other multiword expressions, and their representation in terminology resources raise many questions. This article examines some problems related to the traditional recording in terminology resources which basically consists in creating separate entries for multiword terms. It then compares two alternative approaches: 1. a lexical approach that records different kinds of multiword expressions as subentries; and 2. a construction-based approach that captures sets of multiword expressions as patterns. The two methods are illustrated with environment terms. The comparison shows that the construction-based approach is very promising as that it can prevent some of the shortcomings of the other ones. A proposal for its implementation is presented.
Naya, Ares LLop; Casademont, Anna Joan
L’adquisició dels quantificadors de polaritat gens/cap/res en aprenents de català com a llengua addicional. Estudi empíric i implicacions per a l’ensenyament Miscellaneous
2025.
@misc{llopnayaaresLadquisicioDelsQuantificadors2025,
title = {L’adquisició dels quantificadors de polaritat gens/cap/res en aprenents de català com a llengua addicional. Estudi empíric i implicacions per a l’ensenyament},
author = {Ares LLop Naya and Anna Joan Casademont},
year = {2025},
date = {2025-11-01},
address = {Newcastle},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
L'Homme, Marie-Claude
La terminologie : une discipline linguistique au service d'applications diverses Miscellaneous
2025.
@misc{lhommeTerminologieDisciplineLinguistique2025,
title = {La terminologie : une discipline linguistique au service d'applications diverses},
author = {Marie-Claude L'Homme},
year = {2025},
date = {2025-11-01},
address = {Québec},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
Larivière-Langlois, Mylène
Developing Gender-Neutral Terminology for Healthcare : A Comparative Analysis of Inclusive Writing in French Miscellaneous
2025.
@misc{lariviere-langloisDevelopingGenderNeutralTerminology2025,
title = {Developing Gender-Neutral Terminology for Healthcare : A Comparative Analysis of Inclusive Writing in French},
author = {Mylène Larivière-Langlois},
year = {2025},
date = {2025-10-01},
address = {Vilnius, Lithuanie},
series = {6th Edition},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
L'Homme, Marie-Claude; Frassi, Paolo
Polysémie et autres perspectives sur le sens en terminologie, numéro spécial de la revue Repères-DORIF Journal Article
In: Repères-DORIF, 2025, ISSN: 2281-3020.
@article{lhommePolysemieAutresPerspectives2025,
title = {Polysémie et autres perspectives sur le sens en terminologie, numéro spécial de la revue Repères-DORIF},
author = {Marie-Claude L'Homme and Paolo Frassi},
url = {https://www.dorif.it/reperes/marie-claude-lhomme-paolo-frassi-polysemie-et-autres-perspectives-sur-le-sens-en-terminologie/},
issn = {2281-3020},
year = {2025},
date = {2025-10-01},
journal = {Repères-DORIF},
publisher = {Centro di Documentazione e di Ricerca per la Didattica delle Lingua Francese nell’Università italiana},
series = {En termes de polysémie. Sens et polysémie dans les domaines de spécialité, hors série},
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Frassi, Paolo; L'Homme, Marie-Claude
En termes de polysémie. Sens et polysémie dans les domaines de spécialité, numéro spécial Journal Article
In: Repères-DORIF, no. Numéro spécial, 2025, ISSN: 2281-3020.
@article{frassiTermesPolysemieSens2025,
title = {En termes de polysémie. Sens et polysémie dans les domaines de spécialité, numéro spécial},
author = {Paolo Frassi and Marie-Claude L'Homme},
url = {https://www.dorif.it/reperes/marie-claude-lhomme-paolo-frassi-polysemie-et-autres-perspectives-sur-le-sens-en-terminologie/},
issn = {2281-3020},
year = {2025},
date = {2025-10-01},
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Petrov, Alexander; Venant, Antoine; Lareau, François; Lepage, Yves; Langlais, Philippe
ALF: A Fine-Grained French Analogical Dataset for Evaluating Lexical Knowledge of Large Language Models Proceedings Article
In: Proceedings of the 28th European Conference on Artificial Intelligence, Bologna, Italia, 2025.
@inproceedings{petrov_alf_2025b,
title = {ALF: A Fine-Grained French Analogical Dataset for Evaluating Lexical Knowledge of Large Language Models},
author = {Alexander Petrov and Antoine Venant and François Lareau and Yves Lepage and Philippe Langlais},
year = {2025},
date = {2025-10-01},
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Martín, Antonio San; Trekker, Catherine
Discovering hyponymic knowledge patterns in English Journal Article
In: Terminology, 2025, ISSN: 0929-9971, 1569-9994.
@article{sanmartinDiscoveringHyponymicKnowledge2025,
title = {Discovering hyponymic knowledge patterns in English},
author = {Antonio San Martín and Catherine Trekker},
url = {http://www.jbe-platform.com/content/journals/10.1075/term.25022.san},
doi = {10.1075/term.25022.san},
issn = {0929-9971, 1569-9994},
year = {2025},
date = {2025-10-01},
urldate = {2025-10-30},
journal = {Terminology},
abstract = {Abstract
Identifying hyponymy is essential in terminology work. This article addresses the lack of a comprehensive
inventory of hyponymic knowledge patterns (KPs) in English by presenting a robust methodology for their collection. Drawing on six
complementary strategies — literature review, machine translation, parallel corpora, human translation, bootstrapping, and
generative artificial intelligence — the study identified and validated 110 distinct English hyponymic patterns, many of which had
not been previously documented. These patterns will serve to update the English version of the EcoLexicon Semantic Sketch Grammar
(ESSG-en), a KP-based tool for extracting semantic relations from corpora in Sketch Engine. The findings highlight the strengths
and limitations of each strategy and underscore the value of combining methods to achieve coverage. Ultimately, this research
fills a significant gap by delivering the most extensive list of English hyponymic patterns to date.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Abstract
Identifying hyponymy is essential in terminology work. This article addresses the lack of a comprehensive
inventory of hyponymic knowledge patterns (KPs) in English by presenting a robust methodology for their collection. Drawing on six
complementary strategies — literature review, machine translation, parallel corpora, human translation, bootstrapping, and
generative artificial intelligence — the study identified and validated 110 distinct English hyponymic patterns, many of which had
not been previously documented. These patterns will serve to update the English version of the EcoLexicon Semantic Sketch Grammar
(ESSG-en), a KP-based tool for extracting semantic relations from corpora in Sketch Engine. The findings highlight the strengths
and limitations of each strategy and underscore the value of combining methods to achieve coverage. Ultimately, this research
fills a significant gap by delivering the most extensive list of English hyponymic patterns to date.
Identifying hyponymy is essential in terminology work. This article addresses the lack of a comprehensive
inventory of hyponymic knowledge patterns (KPs) in English by presenting a robust methodology for their collection. Drawing on six
complementary strategies — literature review, machine translation, parallel corpora, human translation, bootstrapping, and
generative artificial intelligence — the study identified and validated 110 distinct English hyponymic patterns, many of which had
not been previously documented. These patterns will serve to update the English version of the EcoLexicon Semantic Sketch Grammar
(ESSG-en), a KP-based tool for extracting semantic relations from corpora in Sketch Engine. The findings highlight the strengths
and limitations of each strategy and underscore the value of combining methods to achieve coverage. Ultimately, this research
fills a significant gap by delivering the most extensive list of English hyponymic patterns to date.
Petrov, Alexander; Venant, Antoine; Lareau, François; Lepage, Yves; Langlais, Philippe
ALF: A Fine-Grained French Analogical Dataset for Evaluating Lexical Knowledge of Large Language Models Proceedings Article
In: Proceedings of the 28th European Conference on Artificial Intelligence, Bologna, Italia, 2025.
@inproceedings{petrov_alf_2025,
title = {ALF: A Fine-Grained French Analogical Dataset for Evaluating Lexical Knowledge of Large Language Models},
author = {Alexander Petrov and Antoine Venant and François Lareau and Yves Lepage and Philippe Langlais},
year = {2025},
date = {2025-10-01},
booktitle = {Proceedings of the 28th European Conference on Artificial Intelligence},
address = {Bologna, Italia},
keywords = {},
pubstate = {published},
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Li, Shuxu; Venant, Antoine; Lareau, François; Langlais, Philippe
Assessing LLMs' Understanding of Structural Contrasts in the Lexicon Proceedings Article
In: Proceedings of the 16th International Conference on Computational Semantics (IWCS), Düsseldorf, Germany, 2025.
@inproceedings{liAssessingLLMsUnderstanding2025,
title = {Assessing LLMs' Understanding of Structural Contrasts in the Lexicon},
author = {Shuxu Li and Antoine Venant and François Lareau and Philippe Langlais},
year = {2025},
date = {2025-09-01},
booktitle = {Proceedings of the 16th International Conference on Computational Semantics (IWCS)},
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Petrov, Alexander; Mancas, Alessandra Thais; Binet, Viviane; Venant, Antoine; Lareau, François; Lepage, Yves; Langlais, Philippe
Q&A-LF: A French Question-Answering Benchmark for Measuring Fine-Grained Lexical Knowledge Proceedings Article
In: Proceedings of the 15th International Conference on Recent Advances in Natural Language Processing, Varna, Bulgaria, 2025.
@inproceedings{petrovQALFFrenchQuestionAnswering2025,
title = {Q&A-LF: A French Question-Answering Benchmark for Measuring Fine-Grained Lexical Knowledge},
author = {Alexander Petrov and Alessandra Thais Mancas and Viviane Binet and Antoine Venant and François Lareau and Yves Lepage and Philippe Langlais},
year = {2025},
date = {2025-09-01},
booktitle = {Proceedings of the 15th International Conference on Recent Advances in Natural Language Processing},
address = {Varna, Bulgaria},
keywords = {},
pubstate = {published},
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}
Casademont, Anna Joan; Gagné, Nancy; Castellanas, Èric Viladrich
Online microlearning resources for Japanese learners of Catalan as an additional language: Research-base work to promote teachers' empowerment Miscellaneous
2025.
@misc{joancasademontOnlineMicrolearningResources2025,
title = {Online microlearning resources for Japanese learners of Catalan as an additional language: Research-base work to promote teachers' empowerment},
author = {Anna Joan Casademont and Nancy Gagné and Èric Viladrich Castellanas},
year = {2025},
date = {2025-09-01},
address = {Kyoto},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
Casademont, Anna Joan
L’interès i la curiositat entre comunitats i llengües distants: estratègies de dinamització Miscellaneous
2025.
@misc{joancasademontLinteresCuriositatEntre2025,
title = {L’interès i la curiositat entre comunitats i llengües distants: estratègies de dinamització},
author = {Anna Joan Casademont},
year = {2025},
date = {2025-09-01},
address = {Kyoto},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
Venant, Antoine; Suzuki, Yutaka
On the relative impact of categorical and semantic information on the induction of self-embedding structures Proceedings Article
In: Bernard, Timothée; Mickus, Timothee (Ed.): Proceedings of the Second Workshop on the Bridges and Gaps between Formal and Computational Linguistics (BriGap-2), pp. 72–89, Association for Computational Linguistics, Düsseldorf, Germany, 2025, ISBN: 979-8-89176-317-3.
@inproceedings{venantRelativeImpactCategorical2025,
title = {On the relative impact of categorical and semantic information on the induction of self-embedding structures},
author = {Antoine Venant and Yutaka Suzuki},
editor = {Timothée Bernard and Timothee Mickus},
url = {https://aclanthology.org/2025.brigap-1.8/},
isbn = {979-8-89176-317-3},
year = {2025},
date = {2025-09-01},
booktitle = {Proceedings of the Second Workshop on the Bridges and Gaps between Formal and Computational Linguistics (BriGap-2)},
pages = {72–89},
publisher = {Association for Computational Linguistics},
address = {Düsseldorf, Germany},
abstract = {We investigate the impact of center embedding and selectional restrictions on neural latent tree models' tendency to induce self-embedding structures. To this aim we compare their behavior in different controlled artificial environments involving noun phrases modified by relative clauses, with different quantity of available training data. Our results provide evidence that the existence of multiple center self-embedding is a stronger incentive than selectional restrictions alone, but that the combination of both is the best incentive overall. We also show that different architectures benefit very differently from these incentives.},
keywords = {},
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We investigate the impact of center embedding and selectional restrictions on neural latent tree models' tendency to induce self-embedding structures. To this aim we compare their behavior in different controlled artificial environments involving noun phrases modified by relative clauses, with different quantity of available training data. Our results provide evidence that the existence of multiple center self-embedding is a stronger incentive than selectional restrictions alone, but that the combination of both is the best incentive overall. We also show that different architectures benefit very differently from these incentives.
Petrov, Alexander; Mancas, Alessandra Thais; Binet, Viviane; Venant, Antoine; Lareau, François; Lepage, Yves; Langlais, Philippe
Q&A-LF: A French Question-Answering Benchmark for Measuring Fine-Grained Lexical Knowledge Proceedings Article
In: Proceedings of the 15th International Conference on Recent Advances in Natural Language Processing, Varna, Bulgaria, 2025.
@inproceedings{petrov_q-lf_2025,
title = {Q&A-LF: A French Question-Answering Benchmark for Measuring Fine-Grained Lexical Knowledge},
author = {Alexander Petrov and Alessandra Thais Mancas and Viviane Binet and Antoine Venant and François Lareau and Yves Lepage and Philippe Langlais},
year = {2025},
date = {2025-09-01},
booktitle = {Proceedings of the 15th International Conference on Recent Advances in Natural Language Processing},
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Li, Shuxu; Venant, Antoine; Lareau, François; Langlais, Philippe
Assessing LLMs' Understanding of Structural Contrasts in the Lexicon Proceedings Article
In: Proceedings of the 16th International Conference on Computational Semantics (IWCS), Düsseldorf, Germany, 2025.
@inproceedings{li_assessing_2025,
title = {Assessing LLMs' Understanding of Structural Contrasts in the Lexicon},
author = {Shuxu Li and Antoine Venant and François Lareau and Philippe Langlais},
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Casademont, Anna Joan; Gagné, Nancy
Le microapprentissage comme outil pédagogique en contexte d’enseignement d’une langue minoritaire Miscellaneous
2025.
@misc{joancasademontMicroapprentissageCommeOutil2025,
title = {Le microapprentissage comme outil pédagogique en contexte d’enseignement d’une langue minoritaire},
author = {Anna Joan Casademont and Nancy Gagné},
year = {2025},
date = {2025-08-01},
address = {Québec},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
Bouebdelli, Aya; Anctil, Dominic
Rétroactions des enseignant·es en lien avec le vocabulaire en production écrite : comment mieux soutenir les élèves pour améliorer la dimension lexicale de leurs écrits? Miscellaneous
2025.
@misc{bouebdelliRetroactionsEnseignantesLien2025,
title = {Rétroactions des enseignant·es en lien avec le vocabulaire en production écrite : comment mieux soutenir les élèves pour améliorer la dimension lexicale de leurs écrits?},
author = {Aya Bouebdelli and Dominic Anctil},
year = {2025},
date = {2025-07-01},
address = {Fribourg, Suisse},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
Anctil, Dominic; Proulx, Caroline; Bouebdelli, Aya
L'enseignement direct de mots ciblés dans des œuvres jeunesse à l'éducation préscolaire en milieu défavorisé : quels apprentissages chez les enfants et quelles pistes pour l'enseignement? Miscellaneous
2025.
@misc{anctilLenseignementDirectMots2025,
title = {L'enseignement direct de mots ciblés dans des œuvres jeunesse à l'éducation préscolaire en milieu défavorisé : quels apprentissages chez les enfants et quelles pistes pour l'enseignement?},
author = {Dominic Anctil and Caroline Proulx and Aya Bouebdelli},
year = {2025},
date = {2025-07-01},
address = {Fribourg, Suisse},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
Anctil, Dominic; Bouebdelli, Aya; Proulx, Caroline
Supporting Vocabulary Development in Disadvantaged Environments: Fostering Inclusive Practices through Collaboration Miscellaneous
2025.
@misc{anctilSupportingVocabularyDevelopment2025,
title = {Supporting Vocabulary Development in Disadvantaged Environments: Fostering Inclusive Practices through Collaboration},
author = {Dominic Anctil and Aya Bouebdelli and Caroline Proulx},
year = {2025},
date = {2025-07-01},
address = {Bologne, Italie},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
Anctil, Dominic; Bissonnette, Karine
Le Référentiel québécois de profils de compétences en français de métiers et professions : processus de développement et applications didactiques d’un outil d’intégration linguistique Miscellaneous
2025.
@misc{anctilReferentielQuebecoisProfils2025,
title = {Le Référentiel québécois de profils de compétences en français de métiers et professions : processus de développement et applications didactiques d’un outil d’intégration linguistique},
author = {Dominic Anctil and Karine Bissonnette},
year = {2025},
date = {2025-07-01},
address = {Besançon, Suisse},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
St-Gelais, Myriam; L'Homme, Marie-Claude; Mollen, Yvette
Le projet Uauitamutau assi. Terminologie de l’environnement en langue innue (innu-aimun) Miscellaneous
2025.
@misc{st-gelaisProjetUauitamutauAssi2025,
title = {Le projet Uauitamutau assi. Terminologie de l’environnement en langue innue (innu-aimun)},
author = {Myriam St-Gelais and Marie-Claude L'Homme and Yvette Mollen},
url = {https://www.uottawa.ca/research-innovation/sites/g/files/bhrskd326/files/2025-06/Programme_Colloque%202025%204.pdf},
year = {2025},
date = {2025-06-01},
address = {University of Ottawa, Ottawa},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
St-Gelais, Myrriam; L'Homme, Marie-Claude; Mollen, Yvette
Le projet Uauitamutau assi. Terminologie de l’environnement en langue innue (innu-aimun) Proceedings Article
In: University of Ottawa, Ottawa, 2025.
@inproceedings{st-gelais_projet_2025,
title = {Le projet Uauitamutau assi. Terminologie de l’environnement en langue innue (innu-aimun)},
author = {Myrriam St-Gelais and Marie-Claude L'Homme and Yvette Mollen},
url = {https://www.uottawa.ca/research-innovation/sites/g/files/bhrskd326/files/2025-06/Programme_Colloque%202025%204.pdf},
year = {2025},
date = {2025-06-01},
address = {University of Ottawa, Ottawa},
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Anctil, Dominic; Bouebdelli, Aya; Proulx, Caroline
Recherche collaborative sur le développement du vocabulaire au 1er cycle primaire : évolution des conceptions et des pratiques des enseignant.e.s Miscellaneous
2025.
@misc{anctilRechercheCollaborativeDeveloppement2025,
title = {Recherche collaborative sur le développement du vocabulaire au 1er cycle primaire : évolution des conceptions et des pratiques des enseignant.e.s},
author = {Dominic Anctil and Aya Bouebdelli and Caroline Proulx},
year = {2025},
date = {2025-05-01},
address = {Montréal, Canada},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
Anctil, Dominic; Proulx, Caroline; Bouebdelli, Aya
Habiletés définitionnelles des enfants à l’éducation préscolaire : analyse qualitative de réponses à une tâche d’explication de mots ciblés dans des séquences d’enseignement direct Miscellaneous
2025.
@misc{anctilHabiletesDefinitionnellesEnfants2025,
title = {Habiletés définitionnelles des enfants à l’éducation préscolaire : analyse qualitative de réponses à une tâche d’explication de mots ciblés dans des séquences d’enseignement direct},
author = {Dominic Anctil and Caroline Proulx and Aya Bouebdelli},
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Boucebha, Lina; Anctil, Dominic
Ébauche d'une séquence didactique pour une démarche intégrée d'enseignement des champs lexicaux au 3e cycle du primaire Miscellaneous
2025.
@misc{boucebhaEbaucheDuneSequence2025,
title = {Ébauche d'une séquence didactique pour une démarche intégrée d'enseignement des champs lexicaux au 3e cycle du primaire},
author = {Lina Boucebha and Dominic Anctil},
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Proulx, Caroline; Anctil, Dominic
Le développement de la sensibilité lexicale en milieu défavorisé : une avenue prometteuse Miscellaneous
2025.
@misc{proulxDeveloppementSensibiliteLexicale2025,
title = {Le développement de la sensibilité lexicale en milieu défavorisé : une avenue prometteuse},
author = {Caroline Proulx and Dominic Anctil},
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Terryn, Ayla Rigouts; Drouin, Patrick
Introduction to the special issue on Computational Terminology Journal Article
In: Terminology. International Journal of Theoretical and Applied Issues in Specialized Communication, vol. 31, no. 1, pp. 1–4, 2025, ISSN: 0929-9971, 1569-9994.
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L'Homme, Marie-Claude
La terminologie en 2025. Parcours méthodologiques (et automatisés) au service d’applications diverses Miscellaneous
2025.
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title = {La terminologie en 2025. Parcours méthodologiques (et automatisés) au service d’applications diverses},
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Terryn, Ayla Rigouts; (eds) Drouin, Patrick
Terminology. Special issue. Computational Terminology Journal Article
In: 2025.
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title = {Terminology. Special issue. Computational Terminology},
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Welcome to e-content platform of John Benjamins Publishing Company. Here you can find all of our electronic books and journals, for purchase and download or subscriber access.
Terryn, Ayla Rigouts; Drouin, Patrick
Introduction to the special issue on Computational Terminology Journal Article
In: Terminology. International Journal of Theoretical and Applied Issues in Specialized Communication, vol. 31, no. 1, pp. 1–4, 2025, ISSN: 0929-9971, 1569-9994.
@article{terryn_introduction_2025,
title = {Introduction to the special issue on Computational Terminology},
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doi = {10.1075/term.00081.rig},
issn = {0929-9971, 1569-9994},
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L'Homme, Marie-Claude
La terminologie en 2025. Parcours méthodologiques (et automatisés) au service d’applications diverses Miscellaneous
2025.
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L'Homme, Marie-Claude
Frame Semantics for Domain-specific Resources: why it is a good idea and some challenges Miscellaneous
2025.
@misc{lhommeFrameSemanticsDomainspecific2025,
title = {Frame Semantics for Domain-specific Resources: why it is a good idea and some challenges},
author = {Marie-Claude L'Homme},
year = {2025},
date = {2025-03-01},
address = {Keio University, Yokohama, Japan},
abstract = {Developers of domain-specific resources have referred to Frame Semantics (Fillmore 1982; Fillmore and Baker 2010) and FrameNet (Ruppenhoffer et al. 2016) since the 2000s and have done so in a variety of domains including but not limited to football (Schmidt 2009), adventure tourism (Durán-Muñoz and L’Homme 2020) and medicine (Castaño and Verdaguer 2024). The theoretical and methodological principles on which framenets are based have proven useful for capturing the linguistic properties of terms and connect these properties to the conceptual background of specialized domains. They also help better highlight how knowledge is conceptualized from the perspective of specialized areas, conceptualizations which might differ from the way everyday situations are considered (see Fillmore 1982 on INNOCENT and GUILTY). That said, adaptations are necessary when applying these principles to specialized knowledge which can depend on the field itself or the specific objectives for which resources are developed.
In this talk, I will first briefly describe the kind of data that domain-specific resource developers typically
deal with, i.e. single-word and multi-word terms, as well as collocations, and emphasize their efforts to connect this linguistic material to the knowledge structure of specialized domains. I will also say a few words about the methods used most often by developers and some of their limitations. I will then explain why Frame Semantics can help address some of these limitations and show how domain-specific framenets differ from “general-language” ones in terms of lexical content, frames and relations between frames. I will also mention some challenges that domain-specific framenet developers are confronted with, such as heavy reliance on corpus data due to the fact that developers are seldom domain experts, small-size corpora (at least when compared with corpora used by lexicographers) and thus reduced access to tools that learn from large amounts of data. I will focus on the application of
Frame Semantics and the FrameNet methodology to the development of multilingual resources in the
field of the environment. The project has been under way since around 2010 (Framed DiCoEnviro 2025;
L’Homme et al. 2020) and led to the description of terms and frames in English, French, Chinese, Italian,
Portuguese, and Spanish.
I will then focus on a new area of research for domain-specific framenet developers, i.e. a method for capturing specialized-frame-evoking multiword units that have been labeled as multiword terms and/or
collocations (e.g. coastal ecosystem, vulnerable habitat, electric vehicle). Although often compositional, these multiword units have often been listed separately in domain-specific resources. The method I suggest relies on the definition of patterns (loosely based on construction grammar: Hoffmann 2022; Hoffmann and Trousdale 2013) and provides for a generalized account of multiword units in resources. I will conclude by mentioning a few areas that require further investigation but that could still rely on Frame Semantics: capturing differences between text genres in specialized domains (e.g. popularization vs. scientific), a better understanding of domain-specific conceptualizations against “everyday” ones,
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Developers of domain-specific resources have referred to Frame Semantics (Fillmore 1982; Fillmore and Baker 2010) and FrameNet (Ruppenhoffer et al. 2016) since the 2000s and have done so in a variety of domains including but not limited to football (Schmidt 2009), adventure tourism (Durán-Muñoz and L’Homme 2020) and medicine (Castaño and Verdaguer 2024). The theoretical and methodological principles on which framenets are based have proven useful for capturing the linguistic properties of terms and connect these properties to the conceptual background of specialized domains. They also help better highlight how knowledge is conceptualized from the perspective of specialized areas, conceptualizations which might differ from the way everyday situations are considered (see Fillmore 1982 on INNOCENT and GUILTY). That said, adaptations are necessary when applying these principles to specialized knowledge which can depend on the field itself or the specific objectives for which resources are developed.
In this talk, I will first briefly describe the kind of data that domain-specific resource developers typically
deal with, i.e. single-word and multi-word terms, as well as collocations, and emphasize their efforts to connect this linguistic material to the knowledge structure of specialized domains. I will also say a few words about the methods used most often by developers and some of their limitations. I will then explain why Frame Semantics can help address some of these limitations and show how domain-specific framenets differ from “general-language” ones in terms of lexical content, frames and relations between frames. I will also mention some challenges that domain-specific framenet developers are confronted with, such as heavy reliance on corpus data due to the fact that developers are seldom domain experts, small-size corpora (at least when compared with corpora used by lexicographers) and thus reduced access to tools that learn from large amounts of data. I will focus on the application of
Frame Semantics and the FrameNet methodology to the development of multilingual resources in the
field of the environment. The project has been under way since around 2010 (Framed DiCoEnviro 2025;
L’Homme et al. 2020) and led to the description of terms and frames in English, French, Chinese, Italian,
Portuguese, and Spanish.
I will then focus on a new area of research for domain-specific framenet developers, i.e. a method for capturing specialized-frame-evoking multiword units that have been labeled as multiword terms and/or
collocations (e.g. coastal ecosystem, vulnerable habitat, electric vehicle). Although often compositional, these multiword units have often been listed separately in domain-specific resources. The method I suggest relies on the definition of patterns (loosely based on construction grammar: Hoffmann 2022; Hoffmann and Trousdale 2013) and provides for a generalized account of multiword units in resources. I will conclude by mentioning a few areas that require further investigation but that could still rely on Frame Semantics: capturing differences between text genres in specialized domains (e.g. popularization vs. scientific), a better understanding of domain-specific conceptualizations against “everyday” ones,
connecting domain-specific framenets to “general” ones, etc.
In this talk, I will first briefly describe the kind of data that domain-specific resource developers typically
deal with, i.e. single-word and multi-word terms, as well as collocations, and emphasize their efforts to connect this linguistic material to the knowledge structure of specialized domains. I will also say a few words about the methods used most often by developers and some of their limitations. I will then explain why Frame Semantics can help address some of these limitations and show how domain-specific framenets differ from “general-language” ones in terms of lexical content, frames and relations between frames. I will also mention some challenges that domain-specific framenet developers are confronted with, such as heavy reliance on corpus data due to the fact that developers are seldom domain experts, small-size corpora (at least when compared with corpora used by lexicographers) and thus reduced access to tools that learn from large amounts of data. I will focus on the application of
Frame Semantics and the FrameNet methodology to the development of multilingual resources in the
field of the environment. The project has been under way since around 2010 (Framed DiCoEnviro 2025;
L’Homme et al. 2020) and led to the description of terms and frames in English, French, Chinese, Italian,
Portuguese, and Spanish.
I will then focus on a new area of research for domain-specific framenet developers, i.e. a method for capturing specialized-frame-evoking multiword units that have been labeled as multiword terms and/or
collocations (e.g. coastal ecosystem, vulnerable habitat, electric vehicle). Although often compositional, these multiword units have often been listed separately in domain-specific resources. The method I suggest relies on the definition of patterns (loosely based on construction grammar: Hoffmann 2022; Hoffmann and Trousdale 2013) and provides for a generalized account of multiword units in resources. I will conclude by mentioning a few areas that require further investigation but that could still rely on Frame Semantics: capturing differences between text genres in specialized domains (e.g. popularization vs. scientific), a better understanding of domain-specific conceptualizations against “everyday” ones,
connecting domain-specific framenets to “general” ones, etc.
L'Homme, Marie-Claude
Frame Semantics for Domain-specific Resources: why it is a good idea and some challenges Proceedings Article
In: Keio University, Yokohama, Japan, 2025.
@inproceedings{lhomme_frame_2025,
title = {Frame Semantics for Domain-specific Resources: why it is a good idea and some challenges},
author = {Marie-Claude L'Homme},
url = {The 6th International FrameNet Workshop 2025 (IFNW 2025)},
year = {2025},
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abstract = {Developers of domain-specific resources have referred to Frame Semantics (Fillmore 1982; Fillmore and Baker 2010) and FrameNet (Ruppenhoffer et al. 2016) since the 2000s and have done so in a variety of domains including but not limited to football (Schmidt 2009), adventure tourism (Durán-Muñoz and L’Homme 2020) and medicine (Castaño and Verdaguer 2024). The theoretical and methodological principles on which framenets are based have proven useful for capturing the linguistic properties of terms and connect these properties to the conceptual background of specialized domains. They also help better highlight how knowledge is conceptualized from the perspective of specialized areas, conceptualizations which might differ from the way everyday situations are considered (see Fillmore 1982 on INNOCENT and GUILTY). That said, adaptations are necessary when applying these principles to specialized knowledge which can depend on the field itself or the specific objectives for which resources are developed.
In this talk, I will first briefly describe the kind of data that domain-specific resource developers typically
deal with, i.e. single-word and multi-word terms, as well as collocations, and emphasize their efforts to connect this linguistic material to the knowledge structure of specialized domains. I will also say a few words about the methods used most often by developers and some of their limitations. I will then explain why Frame Semantics can help address some of these limitations and show how domain-specific framenets differ from “general-language” ones in terms of lexical content, frames and relations between frames. I will also mention some challenges that domain-specific framenet developers are confronted with, such as heavy reliance on corpus data due to the fact that developers are seldom domain experts, small-size corpora (at least when compared with corpora used by lexicographers) and thus reduced access to tools that learn from large amounts of data. I will focus on the application of
Frame Semantics and the FrameNet methodology to the development of multilingual resources in the
field of the environment. The project has been under way since around 2010 (Framed DiCoEnviro 2025;
L’Homme et al. 2020) and led to the description of terms and frames in English, French, Chinese, Italian,
Portuguese, and Spanish.
I will then focus on a new area of research for domain-specific framenet developers, i.e. a method for capturing specialized-frame-evoking multiword units that have been labeled as multiword terms and/or
collocations (e.g. coastal ecosystem, vulnerable habitat, electric vehicle). Although often compositional, these multiword units have often been listed separately in domain-specific resources. The method I suggest relies on the definition of patterns (loosely based on construction grammar: Hoffmann 2022; Hoffmann and Trousdale 2013) and provides for a generalized account of multiword units in resources. I will conclude by mentioning a few areas that require further investigation but that could still rely on Frame Semantics: capturing differences between text genres in specialized domains (e.g. popularization vs. scientific), a better understanding of domain-specific conceptualizations against “everyday” ones,
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Developers of domain-specific resources have referred to Frame Semantics (Fillmore 1982; Fillmore and Baker 2010) and FrameNet (Ruppenhoffer et al. 2016) since the 2000s and have done so in a variety of domains including but not limited to football (Schmidt 2009), adventure tourism (Durán-Muñoz and L’Homme 2020) and medicine (Castaño and Verdaguer 2024). The theoretical and methodological principles on which framenets are based have proven useful for capturing the linguistic properties of terms and connect these properties to the conceptual background of specialized domains. They also help better highlight how knowledge is conceptualized from the perspective of specialized areas, conceptualizations which might differ from the way everyday situations are considered (see Fillmore 1982 on INNOCENT and GUILTY). That said, adaptations are necessary when applying these principles to specialized knowledge which can depend on the field itself or the specific objectives for which resources are developed.
In this talk, I will first briefly describe the kind of data that domain-specific resource developers typically
deal with, i.e. single-word and multi-word terms, as well as collocations, and emphasize their efforts to connect this linguistic material to the knowledge structure of specialized domains. I will also say a few words about the methods used most often by developers and some of their limitations. I will then explain why Frame Semantics can help address some of these limitations and show how domain-specific framenets differ from “general-language” ones in terms of lexical content, frames and relations between frames. I will also mention some challenges that domain-specific framenet developers are confronted with, such as heavy reliance on corpus data due to the fact that developers are seldom domain experts, small-size corpora (at least when compared with corpora used by lexicographers) and thus reduced access to tools that learn from large amounts of data. I will focus on the application of
Frame Semantics and the FrameNet methodology to the development of multilingual resources in the
field of the environment. The project has been under way since around 2010 (Framed DiCoEnviro 2025;
L’Homme et al. 2020) and led to the description of terms and frames in English, French, Chinese, Italian,
Portuguese, and Spanish.
I will then focus on a new area of research for domain-specific framenet developers, i.e. a method for capturing specialized-frame-evoking multiword units that have been labeled as multiword terms and/or
collocations (e.g. coastal ecosystem, vulnerable habitat, electric vehicle). Although often compositional, these multiword units have often been listed separately in domain-specific resources. The method I suggest relies on the definition of patterns (loosely based on construction grammar: Hoffmann 2022; Hoffmann and Trousdale 2013) and provides for a generalized account of multiword units in resources. I will conclude by mentioning a few areas that require further investigation but that could still rely on Frame Semantics: capturing differences between text genres in specialized domains (e.g. popularization vs. scientific), a better understanding of domain-specific conceptualizations against “everyday” ones,
connecting domain-specific framenets to “general” ones, etc.
In this talk, I will first briefly describe the kind of data that domain-specific resource developers typically
deal with, i.e. single-word and multi-word terms, as well as collocations, and emphasize their efforts to connect this linguistic material to the knowledge structure of specialized domains. I will also say a few words about the methods used most often by developers and some of their limitations. I will then explain why Frame Semantics can help address some of these limitations and show how domain-specific framenets differ from “general-language” ones in terms of lexical content, frames and relations between frames. I will also mention some challenges that domain-specific framenet developers are confronted with, such as heavy reliance on corpus data due to the fact that developers are seldom domain experts, small-size corpora (at least when compared with corpora used by lexicographers) and thus reduced access to tools that learn from large amounts of data. I will focus on the application of
Frame Semantics and the FrameNet methodology to the development of multilingual resources in the
field of the environment. The project has been under way since around 2010 (Framed DiCoEnviro 2025;
L’Homme et al. 2020) and led to the description of terms and frames in English, French, Chinese, Italian,
Portuguese, and Spanish.
I will then focus on a new area of research for domain-specific framenet developers, i.e. a method for capturing specialized-frame-evoking multiword units that have been labeled as multiword terms and/or
collocations (e.g. coastal ecosystem, vulnerable habitat, electric vehicle). Although often compositional, these multiword units have often been listed separately in domain-specific resources. The method I suggest relies on the definition of patterns (loosely based on construction grammar: Hoffmann 2022; Hoffmann and Trousdale 2013) and provides for a generalized account of multiword units in resources. I will conclude by mentioning a few areas that require further investigation but that could still rely on Frame Semantics: capturing differences between text genres in specialized domains (e.g. popularization vs. scientific), a better understanding of domain-specific conceptualizations against “everyday” ones,
connecting domain-specific framenets to “general” ones, etc.
Auclair-Ouellet, Noémie; Lavoie, Alexandra; Bédard, Pascale; Barbeau-Morrison, Alexandra; Drouin, Patrick; Tremblay, Pascale
Expansion of the SyllabO+ corpus and database: Words, lemmas, and morphology Journal Article
In: Behavior Research Methods, vol. 57, no. 1, pp. 47, 2025.
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