Next: Sharing Lexical and
(In the Proceedings of the FLAIRS-96 special track on Information Interchange)
Meaning Representation for Knowledge Sharing in Practical Machine Translation
Kavi Mahesh and Sergei Nirenburg
Computing Research Laboratory
Box 30001, Dept. 3CRL
New Mexico State University
Las Cruces, NM 88003-8001
Ph: (505) 646-5466 Fax: (505) 646-6218
mahesh@crl.nmsu.edu, sergei@crl.nmsu.edu
Abstract:
Knowledge-based machine translation can be viewed as the problem of
extracting and representing the meaning of a text and generating a
translation in a target language using the meaning representation.
Meaning extraction requires the integration of information present
explicitly in a text with common sense and domain knowledge given to
the system. Thus, integrating linguistic knowledge of each language
with general world knowledge is a central problem in machine
translation, especially when more than two languages are involved. In
this article we consider the design of a meaning representation that
enables language-specific lexicons to share knowledge with a
language-independent world model. We illustrate how the underlying
core meaning representation can be enhanced in three different ways to
arrive at lexical, ontological, and text meaning representations. The
meaning representations presented here have been implemented in the
Mikrokosmos machine translation system and used to represent Spanish
and Japanese lexicons in addition to a broad-coverage ontological
world model.
Kavi Mahesh
Mon Nov 20 15:52:08 MST 1995