This repository explores different techiques used for Named Entity Recognition (NER) on the CONLL 2003 Reuters Dataset. The data can be found here: https://www.clips.uantwerpen.be/conll2003/ner/ and is under licence by Reuters.
- Conditional Random Fields [w] (F1=77.73)
- Conditional Random Fields [w-1] (F1=83.54)
- Conditional Random Fields [w-2] (F1=83.25)
- Conditional Random Fields [w-3] (F1=83.91)
- BiLSTM-CRF (Glove 50D) (F1=82.55)
- BiLSTM-CRF (SENNA 50D) (F1=82.79)
- BiLSTM-CRF (Glove + Casing Features) (F1=86.23)
- BiLSTM-CRF (SENNA + Casing Features) (F1=85.35)
- GloVe
- SENNA
- Python 3.6
- NumPy
- Pandas
- scikit-learn
- Tensorflow
- Keras