We are working alongside Aleph Insights and Bricolage in the towards the creation of ARGA. As the development lead of the project we have built a working, deployable system for phase 1 with a view to further develop capability in the next phase and beyond.
ARGA is funded through the Defence and Security Accelerator under the ‘Revolutionise the Human Information Relationship for Defence’ call.
Across the whole of Defence, large amounts of text data are routinely produced in an unstructured format, limiting data retrieval and impeding optimal decision-making. ARGA seeks to reduce the burden this creates at source by intelligently assisting authors to apply meaningful structure to text as they write, ultimately creating an adaptive information bridge between data producers and data consumers.
ARGA focuses on tackling difficult open problems, such as: word/phrase prediction; reconciliation of alternative spellings; word-sense disambiguation; corpus-wide co-reference for entities; automated relationship and event extraction; and the development of self-learning ontologies. Unlike most current attempts to solve these problems, ARGA focuses the ML effort on the report generation stage, rather than waiting until the report has been submitted or an entire corpus created. As such, it facilitates true human-machine teaming, so that data producers and ARGA become co-authors of a report.
ARGA is designed to become a key tool within an integrated information environment. It has the potential to enhance the structure of text data for a wide range of systems used in a variety of defence tasks. Phase 2 will focus on increasing ARGA’s capability and enabling it to interact with other systems, either by providing structured text data or by consuming specialised datasets to improve its ability to learn. We are therefore interested to discuss collaboration with other project teams in order to explore potential integrated tools.
Visit the official ARGA website for more information about the project and the rest of the ARGA team.