An English-to-Turkish interlingual MT system

This paper describes the integration of a Turkish generation system with the KANT knowledge-based machine translation system to produce a prototype English-Turkish interlingua-based machine translation system. These two independently constructed systems were successfully integrated within a period of two months, through development of a module which maps KANT interlingua expressions to Turkish syntactic structures. The combined system is able to translate completely and correctly 44 of 52 benchmark sentences in the domain of broadcast news captions. This study is the first known application of knowledge-based machine translation from English to Turkish, and our initial results show promise for future development. © Springer-Verlag Berlin Heidelberg 1998

Design and Implementation of a Tactical Generator for Turkish, a Free Constituent Order Language

This thesis describes a tactical generator for Turkish, a free constituent order language, in which the order of the constituents may change according to the information structure of the sentences to be generated. In the absence of any information regarding the information structure of a sentence (i.e., topic, focus, background, etc.), the constituents of the sentence obey a default order, but the order is almost freely changeable, depending on the constraints of the text flow or discourse. We have used a recursively structured finite state machine for handling the changes in constituent order, implemented as a right-linear grammar backbone. Our implementation environment is the GenKit system, developed at Carnegie Mellon University--Center for Machine Translation. Morphological realization has been implemented using an external morphological analysis/generation component which performs concrete morpheme selection and handles morphographemic processes.Comment: M.Sc. Thesis submitted to the Department of Computer Engineering and Information Science, Bilkent University, Ankara, Turkey. 146 pages (including title pages). Also available as: ftp://ftp.cs.bilkent.edu.tr/pub/tech-reports/1996/BU-CEIS-9614.ps.

The Computational Analysis of the Syntax and Interpretation of Free Word Order in Turkish

In this dissertation, I examine a language with “free” word order, specifically Turkish, in order to develop a formalism that can capture the syntax and the context-dependent interpretation of “free” word order within a computational framework. In “free” word order languages, word order is used to convey distinctions in meaning that are not captured by traditional truth-conditional semantics. The word order indicates the “information structure”, e.g. what is the “topic” and the “focus” of the sentence. The context-appropriate use of “free” word order is of considerable importance in developing practical applications in natural language interpretation, generation, and machine translation. I develop a formalism called Multiset-CCG, an extension of Combinatory Categorial Grammars, CCGs, (Ades/Steedman 1982, Steedman 1985), and demonstrate its advantages in an implementation of a data-base query system that interprets Turkish questions and generates answers with contextually appropriate word orders. Multiset-CCG is a context-sensitive and polynomially parsable grammar that captures the formal and descriptive properties of “free” word order and restrictions on word order in simple and complex sentences (with discontinuous constituents and long distance dependencies). Multiset-CCG captures the context-dependent meaning of word order in Turkish by compositionally deriving the predicate-argument structure and the information structure of a sentence in parallel. The advantages of using such a formalism are that it is computationally attractive and that it provides a compositional and flexible surface structure that allows syntactic constituents to correspond to information structure constituents. A formalism that integrates information structure and syntax such as Multiset-CCG is essential to the computational tasks of interpreting and generating sentences with contextually appropriate word orders in “free” word order languages