A Named Entity Recognition Tool
Named entity recognition aims to detect entities that refer to people, locations, organizations and similar in a given sentence.
This project involves reimplementing a recent NER tagger that is shown to surpass the state-of-the-art performance for morphologically rich languages [1].
We will employ a software framework that is specific to NLP to easily build, train, evaluate and deploy the new tagger, i.e. Stanza, Flair or Huggingface.
We will also add some new features to exploit all types of word embeddings easily.
The main aim of the project is to build a software project that is easy to maintain and extendable.
It will be hosted on our department's language related tool and corpus repository.
[1] Güngör, O., Uskudarli, S., & Güngör, T. (2018, August). Improving named entity recognition by jointly learning to disambiguate morphological tags. In Proceedings of the 27th International Conference on Computational Linguistics (pp. 2082-2092).