Named Entity Recognition (NER) on Estonian Social Media: A Benchmark Dataset and Baselines
Organization
TartuNLP
Abstract
NER is one of the fundamental tasks in Natural Language Processing (NLP) and it aims at identifying different types of entities within a given text. NER involves recognizing named entities such as person, location, organization, etc. in a segment of text.
This proposal involves: i) creating a benchmark dataset by annotating Estonian tweets, ii) proposing a coarse-grained taxonomy and iii) neural baselines.
Outcome: a benchmark dataset and baselines for Estonian NER in the context of social media data in Estonian.
This proposal involves: i) creating a benchmark dataset by annotating Estonian tweets, ii) proposing a coarse-grained taxonomy and iii) neural baselines.
Outcome: a benchmark dataset and baselines for Estonian NER in the context of social media data in Estonian.
Graduation Theses defence year
2022-2023
Supervisor
Somnath Banerjee
Spoken language (s)
Requirements for candidates
Level
Bachelor, Masters
Keywords
Application of contact
Name
Somnath Banerjee
Phone
E-mail