Abstract of FKI-191-94
Title: Extracting Semantic Features for Aspectual Meanings
from a Syntactic Representation Using Neural Networks
Authors: Gabriele Scheler
Category: Technical Report (Forschungsberichte Künstliche Intelligenz)
Abstract: The main point of this paper is to show how we can extract
semantic features, describing aspectual meanings, from
a syntactic representation.
The goal is to translate English to Russian aspectual
This is realized by a specialized language processing module,
which is based on the concept of vertical modularity.
The results of supervised learning of syntactic-semantic
correspondences using standard back-propagation show that
both learning and generalization to new patterns is successful.
Furthermore, the correct generation of Russian aspect from
the automatically created semantic representations is
Keywords: interpretation of written language, machine translation,
grammar checker, grammatical aspect, vertical modularity,
semantic representation, syntactic representation,
Size: 16 pages
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