Composition models of distributional semantics are used to construct phrase representations from the representations of their words. Composition models are typically situated on two ends of a spectrum. They either have a small number of parameters but compose all phrases in the same way, or they perform word-specific compositions at the cost of a far larger number of parameters. In this paper we propose transformation weighting (TransWeight), a composition model that consistently outperforms existing models on nominal compounds, adjective-noun phrases and adverb-adjective phrases in English, German and Dutch. TransWeight drastically reduces the number of parameters needed compared to the best model in the literature by composing similar words in the same way.
No Word is an Island -- A Transformation Weighting Model for Semantic Composition
Transformation weighting (TransWeight) consistently outperforms existing composition models by efficiently using parameters to represent similar words similarly, enhancing performance on various phrase types across languages.
- Year
- 2019
- Venue
- arXiv 2019
- Authors
- 4
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- Abstract onlyARXIV-DEFAULT
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- Abstract & full text
- arxiv.org/abs/1907.05048ARXIV-DEFAULT
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- Semantic Scholar