Poster by Natali Peeva

Standard approaches to question answering do not readily apply to answering complex policy-related questions. Furthermore, existing models and resources primarily focus on English and general questions.

This poster presents Natali Peeva's approach to investigating to what extent and how can state-of-the-art natural language processing models aid the answering City Council questions within the City of Amsterdam. The methodology can later be applied to any policy-related questions independent of their origin.

This research was conducted by Natali Peeva in collaboration with AI Team, Urban Innovation and R&D, City of Amsterdam.

Involved civil servants: Iva Gornishka

Supervisors: João Pereira & Iva Gornishka

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