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:

1. preProcessing contains the code for dataset parsing. Datasets can be downloaded from the website of Universal Dependencies.

2. dataInfo contains details on data set statistics.

3. 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.

4. Code for MOO based GA feature selection.

5. Code for post processing, visualization, BLEU, Levenshtein and word accuracy calculation can be found in postProcessingAndVisualization.

6. Outputs on the HDTB and UDTB datasets.

7. Outputs for t-SNE plots, GA graphs, and Precision-Recall curves.

MOO optimization

Cubic-spline interpolations for validation accuracies of population: