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- W2071490478 abstract "We automatically classify verbs into lexical semantic classes, based on distributions of indicators of verb alternations, extracted from a very large annotated corpus. We address a problem which is particularly difficult because the verb classes, although semantically different, show similar surface syntactic behavior. Five grammatical features are sufficient to reduce error rate by more than 50% over chance: we achieve almost 70% accuracy in a task whose baseline performance is 34%, and whose expert-based upper bound we calculated at 86.5%. We conclude that corpus-driven extraction of grammatical features is a promising methodology for find-grained verb classification." @default.
- W2071490478 created "2016-06-24" @default.
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- W2071490478 date "2000-01-01" @default.
- W2071490478 modified "2023-09-22" @default.
- W2071490478 title "Automatic lexical acquisition based on statistical distributions" @default.
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- W2071490478 doi "https://doi.org/10.3115/992730.992764" @default.
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