View on GitHub


Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.


Chunking is a shallow form of parsing that identifies continuous spans of tokens that form syntactic units such as noun phrases or verb phrases.


Vinken , 61 years old

Penn Treebank

The Penn Treebank is typically used for evaluating chunking. Sections 15-18 are used for training, section 19 for development, and and section 20 for testing. Models are evaluated based on F1.

Model F1 score Paper / Source  
JMT (Hashimoto et al., 2017) 95.77 A Joint Many-Task Model: Growing a Neural Network for Multiple NLP Tasks  
Low supervision (Søgaard and Goldberg, 2016) 95.57 Deep multi-task learning with low level tasks supervised at lower layers  
Suzuki and Isozaki (2008) 95.15 Semi-Supervised Sequential Labeling and Segmentation using Giga-word Scale Unlabeled Data  
NCRF++ (Yang and Zhang, 2018) 95.06 NCRF++: An Open-source Neural Sequence Labeling Toolkit NCRF++

Go back to the README