We apply machine learning techniques to classify automatically a set of verbs into lexical semantic classes, based on distributional approximations of ...
We apply machine learning techniques to classify automatically a set of verbs into lexical semantic classes, based on distributional approximations of ...
It is concluded that corpus data is a usable repository of verb class information, and that corpus-driven extraction of grammatical features is a promising ...
In this paper, we focus on argument structure—the thematic roles as- signed by a verb to its arguments—as the way in which the relational semantics of the verb ...
We develop a general feature space for automatic classification of verbs into lexical semantic classes. ... distribution approximations of grammatical features ...
We develop a general feature space that can be used for the semantic classification of English verbs. We design a technique to extract these features from a ...
In this work, we develop and evaluate a feature space to support the automatic assignment of verbs into a well-known lexical semantic classification that is ...
In this work, we develop and evaluate a feature space to support the automatic assignment of verbs into a well-known lexical semantic classification that is ...
Sep 1, 2001 · In this work, we report on supervised learning experiments to automatically classify three major types of English verbs, based on their argument structure.
Missing: Grammatical | Show results with:Grammatical
Oct 21, 2022 · The evaluation using Levin-style gold standard classes revealed that information about slot distributions in text was more useful than lexical ...