Bart Desmet author Julia Porcino author Ayah Zirikly author Denis Newman-Griffis author Guy Divita author Elizabeth Rasch author 2020-may text English eng European Language Resources Association Marseille, France conference publication 979-10-95546-62-7 The disability benefits programs administered by the US Social Security Administration (SSA) receive between 2 and 3 million new applications each year. Adjudicators manually review hundreds of evidence pages per case to determine eligibility based on financial, medical, and functional criteria. Natural Language Processing (NLP) technology is uniquely suited to support this adjudication work and is a critical component of an ongoing inter-agency collaboration between SSA and the National Institutes of Health. This NLP work provides resources and models for document ranking, named entity recognition, and terminology extraction in order to automatically identify documents and reports pertinent to a case, and to allow adjudicators to search for and locate desired information quickly. In this paper, we describe our vision for how NLP can impact SSA’s adjudication process, present the resources and models that have been developed, and discuss some of the benefits and challenges in working with large-scale government data, and its specific properties in the functional domain. desmet-etal-2020-development https://www.aclweb.org/anthology/2020.lt4gov-1.1 2020-may 1 6