Easy Natural Language Processing

eznlp is a PyTorch-based package for neural natural language processing, currently supporting:

• Text classification
• Named Entity Recognition
  • Sequence tagging
  • Span classification
  • Boundary Selection
• Relation extraction
• Attribute extraction

Experiment Results

Text Classification

See Text Classification for more details.

Named Entity Recognition

See Named Entity Recognition for more details.

Relation Extraction

See Relation Extraction for more details.

Installation

With pip

$ pip install eznlp

From source

$ python setup.py sdist
$ pip install dist/eznlp-<version>.tar.gz

Running the Code

Text classification

$ python scripts/text_classification.py --dataset <dataset> [options]

Entity recognition

$ python scripts/entity_recognition.py --dataset <dataset> [options]

Relation extraction

$ python scripts/relation_extraction.py --dataset <dataset> [options]

Attribute extraction

$ python scripts/attribute_extraction.py --dataset <dataset> [options]

Citation

If you find our code useful, please cite the following paper:

@article{zhu2021framework,
  title={A Unified Framework of Medical Information Annotation and Extraction for {Chinese} Clinical Text},
  author={Zhu, Enwei and Sheng, Qilin and Yang, Huanwan and Li, Jinpeng},
  journal={Working Paper},
  year={2021}
}

Future Plans

• SoftLexicon
• Radical-Level Features
• Experiments on Chinese NER datasets
• Experiments on text classification datasets
• Focal loss (and combined to CRF?)
• Dice loss
• Relation Extraction
• Span-based models (e.g., SpERT)
• NER / RE as MRC
• Pair selection (multi-head selection; RE for flat entities)
• Data Augmentation
• LR finder for MSRA