3 papers
cs.CL2019
Training Compact Models for Low Resource Entity Tagging using Pre-trained Language Models
Peter Izsak, Shira Guskin, Moshe Wasserblat
Training models on low-resource named entity recognition tasks has been shown to be a challenge, especially in industrial applications where deploying updated models is a continuou…
cs.AI2018
Term Set Expansion based NLP Architect by Intel AI Lab
Jonathan Mamou, Oren Pereg, Moshe Wasserblat +5
We present SetExpander, a corpus-based system for expanding a seed set of terms into amore complete set of terms that belong to the same semantic class. SetExpander implements an i…
cs.AI2018
Term Set Expansion based on Multi-Context Term Embeddings: an End-to-end Workflow
Jonathan Mamou, Oren Pereg, Moshe Wasserblat +7
We present SetExpander, a corpus-based system for expanding a seed set of terms into a more complete set of terms that belong to the same semantic class. SetExpander implements an…