In plain words: A toolkit that wires search and text-reading pieces into one flow, so teams can build, test, and ship question-answering systems. A demo that searches documents and then reads them for answers produced high-quality results in both academic and company-specific settings.
Abstract
This paper introduces a novel orchestration framework, called CFO (COMPUTATION FLOW ORCHESTRATOR), for building, experimenting with, and deploying interactive NLP (Natural Language Processing) and IR (Information Retrieval) systems to production environments. We then demonstrate a question answering system built using this framework which incorporates state-of-the-art BERT based MRC (Machine Reading Comprehension) with IR components to enable end-to-end answer retrieval. Results from the demo system are shown to be high quality in both academic and industry domain specific settings. Finally, we discuss best practices when (pre-)training BERT based MRC models for production systems.
Rishav Chakravarti, Cezar Pendus, Andrzej Sakrajda, Anthony Ferritto, Lin Pan, Michael Glass, Vittorio Castelli, J. William Murdock, Radu Florian, Salim Roukos, Avirup Sil
arXiv:1908.06121 · cs.CL, cs.IR · submitted Aug 16, 2019 · updated Jun 19, 2020
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