Pronoun Resolution in Turkish with Deep Learning

Yıl 2024, Cilt: 17 Sayı: 2, 109 - 119

Mehmet Taze , Senem Kumova Metin

https://doi.org/10.54525/bbmd.1595416

Öz

In language, to avoid repetitive use of a word/phrase, it is common to use pronouns that refer to the corresponding antecedent word/phrase. Matching a pronoun with the antecedent to which it refers is called pronoun resolution. This study evaluates the performance of deep learning methods in pronoun resolution in Turkish texts. Within the scope of the study, a dataset was compiled using 10 Turkish children's stories and 12 features were identified to be used in the experiments. Multilayer perceptron, convolutional and recurrent neural networks were tested in several different configurations with varying numbers of neurons and layers and the performance was measured with F1 score. The results show that the highest performance in Turkish pronoun resolution is achieved by a multilayer perceptron neural network with a medium number of layers using too many neurons.

Anahtar Kelimeler

Natural language processing, Pronoun resolution, Convolutional neural networks, Multilayer Perceptron, Recurrent neural networks

Derin Öğrenme ile Türkçede Adıl Çözümleme

Öz

Dilde, bir sözcüğün/sözcük öbeğinin sürekli tekrar eden kullanımını önlemek için, ilgili öncül sözcüğe/sözcük öbeğine atıfta bulunan adılların kullanımına sık rastlanır. Bir adılın atıfta bulunduğu öncül ile eşleştirilmesi adıl çözümleme olarak adlandırılır. Bu çalışmada Türkçe metinlerde adılların çözümlenmesinde derin öğrenme yöntemlerinin başarımı değerlendirilmiştir. Çalışma kapsamında 10 Türkçe çocuk hikayesi kullanılarak bir veri kümesi derlenmiş, deneylerde kullanılmak üzere 12 öznitelik belirlenmiştir. Çok katmanlı algılayıcı, evrişimsel (konvolüsyonel) ve tekrarlayan sinir ağları nöron ve katman sayılarının değiştiği bir dizi farklı konfigürasyonla uygulanarak F1 ölçüsü ile başarım ölçülmüştür. Sonuçlar, Türkçe adıl çözümlemesinde en yüksek başarımın, çok fazla nöron kullanan orta sayıda katmana sahip çok katmanlı algılayıcı sinir ağı tarafından elde edildiğini göstermiştir.

Anahtar Kelimeler

Doğal dil işleme, Adıl çözümleme, Evrişimsel sinir ağları, Çok katmanlı algılayıcı, Tekrarlayan sinir ağları

Kaynakça

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