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PoS Tagging with Bidirectional Long Short-Term Memory Models

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DEEPtagger

Part-of-Speech Tagging for Icelandic using a Bidirectional Long Short-Term Memory Model with combined Word and Character embeddings

Project report

Training models

A bidirectional LSTM model can be trained with the script train.py.

training

Running ./train.py -h gives information on all possible parameters.

The program requires input corpora to be in the same format as the IFD-training/testing sets, available at http://www.malfong.is/index.php?lang=en&pg=ordtidnibok

Results from experiments with different models, trained on the IFD, are here: https://docs.google.com/spreadsheets/d/1YG8xYaW10x4jvsCFyHkQxdYQLIOFa6WoBUzbA4y4Gtg/edit?usp=sharing

Fetching results during training

During long running training sessions get_results.py was used fetch the latest results and calculate the highest scoring epoch.

get_results

If the parameter -p is added when running the script a plot is provided for the accuracy and avg. loss of all epochs finished sofar.

Trying out the resulting PoS tagger

The script interactive.py trains a model and then allow the user to try out the tagger on sentences he enters. It accepts the same parameters as train.py.

interactive

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