Conference paper (in proceedings)
From 124 million tokens to 1,021 neologisms : a large-scale pipeline for automatic neologism detection
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Rossini, Diego
ORCID
Istituto di argomentazione, linguistica e semiotica (IALS), Facoltà di comunicazione, cultura e società, Università della Svizzera italiana, Svizzera
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van der Plas, Lonneke
ORCID
Istituto di argomentazione, linguistica e semiotica (IALS), Facoltà di comunicazione, cultura e società, Università della Svizzera italiana, Svizzera
Published in:
- Proceedings of the Workshop Neology and Large Language Models. - 2026, p. 1-15
English
We present a scalable, modular pipeline for automatic neologism detection that combines rule-based filtering with LLM classification. The pipeline is grounded in two complementary word-formation frameworks, grammatical and extra-grammatical morphology, which jointly define the scope of what counts as a neologism and inform a four-class classification scheme (NEOLOGISM, ENTITY, FOREIGN, NONE). While designed to be modular and transferable at the architectural level, the pipeline is instantiated on 527 million English-language Reddit posts spanning 2005–2024. From this corpus, we extract 124.6 million unique tokens and reduce them by over 99.99% to yield 1,021 neologism candidates, a set small enough for manual expert verification. Multiple LLMs independently classify each candidate via majority vote, with a final verification step, revealing substantial cross-model disagreement and highlighting the challenge of operationalizing neologism detection at scale. Manual annotation of all 1,021 candidates confirms that 599 (58.7%) are genuine lexical innovations.
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Collections
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Language
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Classification
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Computer science and technology
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Notes
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- The Fifteenth Language Resources and Evaluation Conference (LREC 2026)
- Palma, Mallorca, Spain
- 2026
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License
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Open access status
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gold
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Identifiers
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Persistent URL
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https://n2t.net/ark:/12658/srd1336329
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