Knowledge-Based Question and Answering System for Turkish

A knowledge-based QA system for Turkish is presented in this paper. The developed QA system has two phases: 1° Learning question and constitute two databases named question and answer database. 2° Uses the question and answer databases as knowledge-base for QA operation. The first phase of the project consists of pre-processing (tokenizing of sentences, parsing a word into syllable, phonological testing consonant softening, vowel reduction, haplology, head and tail letters, morphological testing, mumpsimus, foreign words), morphological parsing, finding of roles of words, interpretation of question and answering. All these parts developed according to Turkish grammar. In the first phase the QA system can understand question and answers. Later on, constitutes question and answer parallel corpus in other word data bases. The second phase consist of the same pre-processing then searches for the same and similar question in question database if finds the answer gets from answer database. In order to fine similar question similarity vectors approaches were used.