Design and implementation of a system for mapping text meaning representations to f-structures of Turkish sentences
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Interlingua approach to Machine Translation (MT) aims to achieve the translation task in two independent steps. First, the meanings of source language sentences are represented in a language-independent artificial language. Then, sentences of the target language are generated from those meaning representations. Generation task in this approach is performed in three major steps among which the second step creates the syntactic structure of a sentence from its meaning representation and selects the words to be used in that sentence. This thesis focuses on the design and the implementation of a prototype system that performs this second task. The meaning representation used in this work utilizes a hierarchical world representation, ontology, to denote events and entities, and embeds semantic and pragmatic issues with special frames. The developed system is language-independent and it takes information about the target language from three knowledge resources: lexicon (word knowledge), map-rules (the relation between the meaning representation and the syntactic structure), and target language's syntactic structure representation. It performs two major tasks in processing the meaning representation: lexical selection and mapping the two representations of a sentence . The implemented system is tested on Turkish using small-sized knowledge resources developed for Turkish. The output of the system can be fed as input to a tactical generator, which is developed for Turkish, to produce the final Turkish sentences.
Natural Language Generation
Text Meaning Representation
Syntactic Structure Representation