Browsing by Subject "Computer aided language translation"

Now showing 1 - 4 of 4

Open Access
An English-to-Turkish interlingual MT system
(Springer, 1998-10) Hakkani, Dilek Zeynep; Tür, Gökhan; Oflazer, Kemal; Mitamura, T.; Nyberg, E.H.
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.
Open Access
An ontology-based approach to parsing Turkish sentences
(Springer, 1998-10) Temizsoy, Murat; Çiçekli, ilyas
The main problem with natural language analysis is the ambiguity found in various levels of linguistic information. Syntactic analysis with word senses is frequently not enough to resolve all ambiguities found in a sentence. Although natural languages are highly connected to the real world knowledge, most of the parsing architectures do not make use of it effectively In this paper, a new methodology is proposed for analyzing Turkish sentences which is heavily based on the constraints in the ontology. The methodology also makes use of morphological marks of Turkish which generally denote semantic properties. Analysis aims to find the propositional structure of the input utterance without constructing a deep syntactic tree, instead it utilizes a weak interaction between syntax and semantics. The architecture constructs a specific meaning representation on top of the analyzed propositional structure. © Springer-Verlag Berlin Heidelberg 1998.
Open Access
Ordering translation templates by assigning confidence factors
(Springer Verlag, 1998) Öz, Zeynep; Çiçekli, İlyas
TTL (Translation Template Learner) algorithm learns lexical level correspondences between two translation examples by using analogical reasoning. The sentences used as translation examples have similar and different parts in the source language which must correspond to the similar and different parts in the target language. Therefore these correspondences are learned as translation templates. The learned translation templates are used in the translation of other sentences. However, we need to assign confidence factors to these translation templates to order translation results with respect to previously assigned confidence factors. This paper proposes a method for assigning confidence factors to translation templates learned by the TTL algorithm. Training data is used for collecting statistical information that will be used in confidence factor assignment process. In this process, each template is assigned a confidence factor according to the statistical information obtained from training data. Furthermore, some template combinations are also assigned confidence factors in order to eliminate certain combinations resulting bad translation. © Springer-Verlag Berlin Heidelberg 1998.
Open Access
Parsing Turkish using the lexical functional grammar formalism
(Springer/Kluwer Academic Publishers, 1995) Güngördü, Z.; Oflazer, K.
This paper describes our work on parsing Turkish using the lexical-functional grammar formalism [11]. This work represents the first effort for wide-coverage syntactic parsing of Turkish. Our implementation is based on Tomita's parser developed at Carnegie Mellon University Center for Machine Translation. The grammar covers a substantial subset of Turkish including structurally simple and complex sentences, and deals with a reasonable amount of word order freeness. The complex agglutinative morphology of Turkish lexical structures is handled using a separate two-level morphological analyzer, which has been incorporated into the syntactic parser. After a discussion of the key relevant issues regarding Turkish grammar, we discuss aspects of our system and present results from our implementation. Our initial results suggest that our system can parse about 82% of the sentences directly and almost all the remaining with very minor pre-editing. © 1995 Kluwer Academic Publishers.