Papers by Katarzyna Pruś

    2 papers
    Human Temporal Inferences Go Beyond Aspectual Class (2024.eacl-long)

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    Challenge: Existing work on aspectual classification in English has been motivated as a pre-requisite for Natural Language Understanding (NLU) in cases where temporal reasoning is required.
    Approach: They propose to classify English verb phrases into situation aspect categories by gathering crowd-sourced judgements from non-expert, native English participants.
    Outcome: The proposed approach uses a crowd-sourced dataset from non-expert, native English participants to examine aspectual entailments in English.
    World Knowledge Resolves Some Aspectual Ambiguity (2025.findings-acl)

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    Challenge: Annotating event descriptions with aspectual features is often seen as a pre-requisite to temporal reasoning, however, a recent study has shown that non-experts’ annotations of the aspectual class of English verb phrases can disagree with both expert linguistic annotations and each other.
    Approach: They hypothesized that people use their world knowledge to tacitly conjure their own contexts, leading to disagreement between them.
    Outcome: The results show that the hypothesis explains some of the disagreement, but outputs from GPT-4 are not an accurate predictor of human answers.

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