Papers by Mattia Proietti

1 papers
Does BERT Recognize an Agent? Modeling Dowty’s Proto-Roles with Contextual Embeddings (2022.coling-1)

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Challenge: Contextual embeddings build multidimensional representations of word tokens based on their context of occurrence.
Approach: They propose to map the verb embeddings to an interpretable space of semantic properties built from a linguistic dataset and test their ability to model the semantic properties of the agent of the verbs participating in the alternation.
Outcome: The proposed models can model the semantic properties of the verbs participating in the so-called causative alternation.

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