NLP Architect v0.2

Release v0.2

New Solution

• Term Set Expansion - the task of expanding a given partial set of terms into a more complete set of terms that belong to the same semantic class. This solution demonstrates the usage of NLP Architect models (Word Chunker and NP2Vec) used in an application solution.

New models

• Unsupervised Crosslingual Embeddings model using a GAN to learn a mapping between languages - implemented in Tensorflow
• Language Model (LM) using Temporal Convolution Network (TCN) - implemented in Tensorflow
• Supervised Sentiment Classification - implemented in Keras

Model improvements

• Reading comprehension - refactored to use Tensorflow
• End-to-end Memory Network for Goal Oriented Dialogue - refactored to use Tensorflow
• Word Chunker - refactored to use tf.keras and use state-of-art model
• NP semantic segmentation - refactored to use tf.keras
• Updated CONLL2000, Amazon_Review, PTB, Fasttext, Wikitext-103 and Wikipedia-dump dataset loaders.

New features

• REST server refactored to use hug, new streamlined the UI and improved documentation. See updated documentation for further details.
• Noun Phrase annotator plug-in for spaCy pipeline
• Publications page with relevant material demonstrating the usage of NLP Architect
• Tutorials page with a collection of Jupyter notebook tutorials using NLP Architect models