Density Matrices for Metaphor Understanding
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866917755063631872 |
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| author | Owers, Jay Shutova, Ekaterina Lewis, Martha |
| author_facet | Owers, Jay Shutova, Ekaterina Lewis, Martha |
| contents | In physics, density matrices are used to represent mixed states, i.e. probabilistic mixtures of pure states. This concept has previously been used to model lexical ambiguity. In this paper, we consider metaphor as a type of lexical ambiguity, and examine whether metaphorical meaning can be effectively modelled using mixtures of word senses. We find that modelling metaphor is significantly more difficult than other kinds of lexical ambiguity, but that our best-performing density matrix method outperforms simple baselines as well as some neural language models. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_11846 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Density Matrices for Metaphor Understanding Owers, Jay Shutova, Ekaterina Lewis, Martha Computation and Language In physics, density matrices are used to represent mixed states, i.e. probabilistic mixtures of pure states. This concept has previously been used to model lexical ambiguity. In this paper, we consider metaphor as a type of lexical ambiguity, and examine whether metaphorical meaning can be effectively modelled using mixtures of word senses. We find that modelling metaphor is significantly more difficult than other kinds of lexical ambiguity, but that our best-performing density matrix method outperforms simple baselines as well as some neural language models. |
| title | Density Matrices for Metaphor Understanding |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2408.11846 |