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    Statistical models trained on distributional co-occurrenc... — Carmelics
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    Challenges→Statistical semantics approaches are currently superior to logical systems for practical NLP applications

    Statistical models trained on distributional co-occurrence lack explicit compositional structure and thus cannot in principle generalize to novel logical forms unseen in training data.

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    Key Terms

    Compositional structure(in philosophy of language)
    The idea that the meaning of something complex (like a sentence) is built up from the meanings of its smaller parts (like individual words) and how they combine together.
    Distributional co-occurrence(as used in linguistics and AI)
    The idea that words or concepts that appear near each other in text or data are related in meaning—like how 'coffee' and 'morning' often show up together.
    Generalize(in logical reasoning)
    To apply a principle or rule that works in one case to other similar cases.
    Statistical models(as used in science and data analysis)
    Mathematical tools that use data and probability to describe patterns and make predictions about how things work.
    logical forms

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    (Kantian epistemology)
    The capacities that structure the contents of judgment for Kant, which on the Sellars/McDowell reading also structure sensory experience via application of the categories
    novel(as describing subsequent entities that are created)
    In philosophy, this means genuinely new or original—something that hasn't existed before in that particular way.

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    Statistical semantics approaches are currently superior to logical systems for p...

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