Awesome
Multi-Task Deep Morphological Analyzer
This repo contains the code for our paper entitled Multi Task Deep Morphological Analyzer : Context Aware Neural Joint Morphological Tagging and Lemma Prediction. The Web API service is accessible here.
A sample analysis:
Experiements
Both the directories follow the organization:
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preProcessing contains the code for dataset parsing. Datasets can be downloaded from the website of Universal Dependencies.
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dataInfo contains details on data set statistics.
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Models for all experiments:
- multiTask_with_context4.py hosts the fully BiLSTM model for a CW of 4 words.
- multiTask_with_attention.py hosts the character CNN-RNN based MT-DMA model, as reported in the paper.
- onlyFeatures.py and onlyRoots.py contain the codes for individual learning.
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Code for MOO based GA feature selection.
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Code for post processing, visualization, BLEU, Levenshtein and word accuracy calculation can be found in postProcessingAndVisualization.
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Outputs on the HDTB and UDTB datasets.
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Outputs for t-SNE plots, GA graphs, and Precision-Recall curves.
MOO optimization
Cubic-spline interpolations for validation accuracies of population: