Dependency Parser for Bulgarian
Atanas Atanasov · 2024
This paper delves into the implementation of a Biaffine Attention Model, a sophisticate neural network architecture employed for dependency parsing tasks. Proposed by Dozat and Manning, this model is applied to Bulgarian language processing. The model's training and evaluation are conducted using the Bulgarian Universal Dependencies dataset. The paper offers a comprehensive explanation of the model's architecture and the data preparation process, aiming to demonstrate that for highly inflected languages, the inclusion of two additional input layers - lemmas and language-specific morphological information - is beneficial. The results of the experiments are subsequently presented and discussed. The paper concludes with a reflection on the model's performance and suggestions for potential future work.