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        <title>An Open, Extendible, and Fast Turkish Morphological Analyzer</title>
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        <namePart type="given">Olcay</namePart>
        <namePart type="given">Taner</namePart>
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        <namePart type="given">Begüm</namePart>
        <namePart type="family">Avar</namePart>
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    <name type="personal">
        <namePart type="given">Gökhan</namePart>
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            <title>Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)</title>
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            <namePart type="given">Ruslan</namePart>
            <namePart type="family">Mitkov</namePart>
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            <namePart type="given">Galia</namePart>
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    <abstract>In this paper, we present a two-level morphological analyzer for Turkish. The morphological analyzer consists of five main components: finite state transducer, rule engine for suffixation, lexicon, trie data structure, and LRU cache. We use Java language to implement finite state machine logic and rule engine, Xml language to describe the finite state transducer rules of the Turkish language, which makes the morphological analyzer both easily extendible and easily applicable to other languages. Empowered with the comprehensiveness of a lexicon of 54,000 bare-forms including 19,000 proper nouns, our morphological analyzer presents one of the most reliable analyzers produced so far. The analyzer is compared with Turkish morphological analyzers in the literature. By using LRU cache and a trie data structure, the system can analyze 100,000 words per second, which enables users to analyze huge corpora in a few hours.</abstract>
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    <identifier type="doi">10.26615/978-954-452-056-4_156</identifier>
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%0 Conference Proceedings
%T An Open, Extendible, and Fast Turkish Morphological Analyzer
%A Yıldız, Olcay Taner
%A Avar, Begüm
%A Ercan, Gökhan
%Y Mitkov, Ruslan
%Y Angelova, Galia
%S Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)
%D 2019
%8 September
%I INCOMA Ltd.
%C Varna, Bulgaria
%F yildiz-etal-2019-open
%X In this paper, we present a two-level morphological analyzer for Turkish. The morphological analyzer consists of five main components: finite state transducer, rule engine for suffixation, lexicon, trie data structure, and LRU cache. We use Java language to implement finite state machine logic and rule engine, Xml language to describe the finite state transducer rules of the Turkish language, which makes the morphological analyzer both easily extendible and easily applicable to other languages. Empowered with the comprehensiveness of a lexicon of 54,000 bare-forms including 19,000 proper nouns, our morphological analyzer presents one of the most reliable analyzers produced so far. The analyzer is compared with Turkish morphological analyzers in the literature. By using LRU cache and a trie data structure, the system can analyze 100,000 words per second, which enables users to analyze huge corpora in a few hours.
%R 10.26615/978-954-452-056-4_156
%U https://aclanthology.org/R19-1156
%U https://doi.org/10.26615/978-954-452-056-4_156
%P 1364-1372

Markdown (Informal)

[An Open, Extendible, and Fast Turkish Morphological Analyzer](https://aclanthology.org/R19-1156) (Yıldız et al., RANLP 2019)

• An Open, Extendible, and Fast Turkish Morphological Analyzer (Yıldız et al., RANLP 2019)

ACL

• Olcay Taner Yıldız, Begüm Avar, and Gökhan Ercan. 2019. An Open, Extendible, and Fast Turkish Morphological Analyzer. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019), pages 1364–1372, Varna, Bulgaria. INCOMA Ltd..