My name is Joe Barrow, and I'm an NLP PhD student at the University of Maryland working for Professor Philip Resnik
and Professor Doug Oard
AllenNLP the Hard Way
This series is my AllenNLP tutorial that goes from installation through building a state-of-the-art (or nearly) named entity recognizer. By the end we will have covered dataset readers, Hierarchical LSTMs and BERT, predictors, debugging, and experimental repeatability.
All the code for the tutorial can be found in the associated Github repository.
Covering Installation and Setup (including best practices)
An introduction to Named Entity Recognition (NER) and the CoNLL'03 Dataset.
Building a sequence-tagging LSTM for Named Entity Recognition (NER).
Combining the dataset readers and models to run our first experiment.
Recommendations on how to tackle your own experiments.
Exploring AllenNLP Predictors for using your trained models.
(In Progress) Commong debugging tips, tricks, and tools for AllenNLP and PyTorch.
This series contains summaries of interesting papers.
Summary of paper by Jean Maillard, Stephen Clark, and Dani Yogatama