NLP Architect by Intel AI Lab
Peter Izsak, Anna Bethke, Daniel Korat, Amit Yaccobi, Jonathan Mamou, Shira Guskin, Sharath Nittur Sridhar, Andy Keller, Oren Pereg, Alon Eirew, Sapir Tsabari, Yael Green, Chinnikrishna Kothapalli, Harini Eavani, Moshe Wasserblat, Yinyin Liu, Guy Boudoukh, Ofir Zafrir, Maneesh Tewani · Zenodo (CERN European Organization for Nuclear Research) · 2018
NLP Architect by Intel AI Lab: A Python library for exploring the state-of-the-art deep learning topologies and techniques for natural language processing and natural language understanding. Release v0.3 New Solution Topics and Trend Analysis - extract topics and compare two temporal versions a corpus, highlighting hot and cold trends. New models Sparse GNMT - A Tensorflow implementation of the GNMT model with sparsity and quantization operations integrated. Semantic Relation Identification - Extract semantic relation types of two words or phrases using external resources. Sieve-based Cross Document Coreference - A seive-based model for finding similar entities or events across different documents from the same domain. Improvements Reading comprehension - added inference mode. Sequential models - updated NER, IE, Chunker models to use tf.keras and added CNN-character based feature extractors and improved accuracy of all models. CRF Layer - added native Tensorflow based CRF layer. Word Sense Disambiguation - model updated to use tf.keras. Demo UI - updated demo UI using AngularJS. Installation - improved installation process and added support for CPU/MKL/GPU backends for Tensorflow. NLP Architect cmd - added nlp_architect - a simple command initiator to handle maintenance tasks, see nlp_architect -h for the list of commands. Lots of bug fixes and refactoring.