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Polysemy–-Evidence from Linguistics, Behavioral Science, and Contextualized Language Models

Paper · 2024 · Janosch Haber and Massimo Poesio

Summary

This survey asks how polysemy (a word carrying several distinct but related senses, such as school meaning a building, an administration, a sports team or an institution) is mentally represented and processed, and why simple universal accounts keep falling short. The authors do not introduce a new dataset or model. Instead, they review decades of research from lexicography, theoretical linguistics, psycholinguistics, neuroscience (eye-tracking, EEG, MEG), crowdsourced annotation and computational linguistics, from sense inventories such as WordNet to contextualized models such as BERT. They also propose working definitions of polysemy and its subtypes so that findings can be compared across fields.

Their synthesis has three parts. Classic analyses often rely on vague definitions and hand-picked examples. Linguistic tests clarify single cases but miss many relevant factors. Newer behavioral, annotation and model-based evidence shows sense relatedness forming a continuum, from near-identity to homonym-like distance. The authors therefore favor hybrid accounts that combine underspecification with structure such as sense clusters or hierarchies. For NLP, the survey argues for richer benchmarks that test how large language models handle graded ambiguity.

Key points

  • The survey contrasts two computational traditions. The Sense Enumeration view (Katz and Fodor 1963) underlies WordNet-style inventories, which list every interpretation as a separate sense. The One Representation approach, best known through Pustejovsky's Generative Lexicon (1995), derives all senses from a single entry.
  • Eye-tracking, EEG and MEG studies indicate that polysemes are processed differently from homonyms. Different types of polysemous alternation also differ from one another in processing.
  • Large annotation efforts, such as Camacho-Collados and Pilehvar 2018, Trott and Bergen 2021 and Haber and Poesio 2021, find that annotators separate polysemous senses less consistently than homonymic meanings. BERT partially reproduces these human similarity patterns.
  • Even regular metonymic polysemy covers many alternation types, some well defined and others close to vagueness. Predication order, prototypicality and frequency all affect how such senses behave.
  • The authors name Semantic Change Detection, better brain data and cheap crowdsourcing as promising directions. The paper appeared in Computational Linguistics (2024, DOI 10.1162/coli_a_00500) under CC BY-NC-ND 4.0, with partial funding from the DALI project (ERC grant 695,662).

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

 Institutions

🎓Queen Mary University of LondonLondon · United Kingdom54 works · 3,542 citations🎓Utrecht UniversityUtrecht · Netherlands39 works · 1,603 citations

 Fields, topics and concepts

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 16,039 worksLanguage and Linguistics · 15,891 worksPsychology · 1,552 worksExperimental and Cognitive Psychology · 870 worksNeuroscience · 165 worksCognitive Neuroscience · 164 works

🧭 Topics 3Research subjects and languages the work is about.Language models & pretraining · 3,320 worksLexical semantics & word embeddings · 63 worksPsycholinguistics & language acquisition · 102 works

Cite

Cite as Janosch Haber and Massimo Poesio. 2024. Polysemy–-Evidence from Linguistics, Behavioral Science, and Contextualized Language Models. Computational Linguistics.

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.1162/coli_a_00500

@article{haber2024polysemy,
  title = {{Polysemy–-Evidence from Linguistics, Behavioral Science, and Contextualized Language Models}},
  author = {Janosch Haber and Massimo Poesio},
  journal = {Computational Linguistics},
  year = {2024},
  doi = {10.1162/coli\_a\_00500},
  url = {https://doi.org/10.1162/coli_a_00500}
}

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