Daniel Ziembicki


2023

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Adopting ISO 24617-8 for Discourse Relations Annotation in Polish:Challenges and Future Directions
Sebastian Zurowski | Daniel Ziembicki | Aleksandra Tomaszewska | Maciej Ogrodniczuk | Agata Drozd
Proceedings of the 4th Conference on Language, Data and Knowledge

2019

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Named Entity Recognition - Is There a Glass Ceiling?
Tomasz Stanislawek | Anna Wróblewska | Alicja Wójcicka | Daniel Ziembicki | Przemyslaw Biecek
Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL)

Recent developments in Named Entity Recognition (NER) have resulted in better and better models. However, is there a glass ceiling? Do we know which types of errors are still hard or even impossible to correct? In this paper, we present a detailed analysis of the types of errors in state-of-the-art machine learning (ML) methods. Our study illustrates weak and strong points of the Stanford, CMU, FLAIR, ELMO and BERT models, as well as their shared limitations. We also introduce new techniques for improving annotation, training process, and for checking model quality and stability.