Cross-lingual Named Entity Recognition and Relation Extraction

Student: Akhtariev Ruslan

Supervisor: Ekaterina Artemova

Educational Programme: Applied Mathematics and Information Science (Bachelor)

Year of Graduation: 2021

In this work we are going to study the ability of different Machine Reading Comprehension language models to be transferred into other languages. Named Entity Recognition and Relation Extraction are one of the most popular tasks in Natural Language Processing and in the past years there were many successful attempts to solve them using Machine Reading Comprehension models. We are going to transfer two such models into Russian language and conduct experiments on different datasets with different training options. Also, one of the main points of the work will be studying in what way and how much different amount of fine-tuning affects models’ results in source and target languages.

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