Verb Classification Across Languages

Verb classes within and across languages

Any attempt to characterize valency patterns within and across languages confronts the phenomenon of verb or valency classes: sets of semantically-related verbs sharing a range of linguistic properties, such as the possible realizations of their arguments and the particular interpretation associated with each possible argument realization. The Leipzig Valency Classes Project provides an excelle...

Metacognitive (Rending) Strategies Across Languages and Techniques

Events and verb classification*

The prevailing approach to understanding the syntactic mapping of arguments and argument alternations is to assume that verbs are organized into semantically distinct verb classes and that class membership determines the grammaticality of argument alternations. This paper presents syntactic evidence that verb-class membership cannot explain the causative and locative alternations, and that alte...

Why verb - initial languages are not frequent

In our simulations with simple recurrent networks we demonstrate that small artificial languages are learnt worse or better depending on their basic word order. We show that verb-initial languages are difficult to learn, reflecting the lower frequency of verb-initial natural languages. We try to go beyond mere simulations proposing two objective mathematical measures to explain our results.

Automatic Verb Classification Using a

Automatic Verb Classification Using a General Feature Space Eric Joanis Master of Science Graduate Department of Computer Science University of Toronto 2002 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 large corpus of English, while trying to maintain portability to other languages—th...