Named Entity Recognition project that reached 70.9% F1-score on the SemEval 2022 MultiCoNER English dataset. I developed it in Pytorch using BiLSTM, CRF, word embeddings and PoS embeddings. This was the first homework of the NLP 2022 course at Sapienza University of Rome.
- Roberto Navigli
For more details, read the Report