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Development of a Software Tool for Named Entity Recognition

Student: Mikhail Myazin

Supervisor: Eduard Klyshinskiy

Faculty: HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE)

Educational Programme: Applied Mathematics (Bachelor)

Year of Graduation: 2020

In this work, we observe different approaches to one of the tasks of natural language processing that is named entities recognition. This work aims to analyze methods of named entities recognition without the usage of any external sources of linguistic information or subject domain. We developed and evaluated different machine learning approaches in combination with variants of word embeddings and language models. As the result, it was determined that the model using the combination of CNN, BiLSTM and deep contextualized Flair embeddings and CRF layer shows the best result. Lastly, we developed a software tool based on that model.

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