Using an NLP Q&A System To Study Climate Hazards and Nature-Based Solutions

The above snapshot is a classic example of how our Q&A system works. Users can ask questions pertaining to climate hazards (or their solutions) and the model will carve out relevant answers from the collected Knowledge Base.

The model suggests ‘Mangrove forests’, ‘improved river-flow regulation’,and ‘stone bunds’ to tackle floods.

What’s more? We also pinpoint the context that was used to generate the answer along with a hyperlink for those who want to go into more depth (panaroma.solutions in this case).

Let’s explore why we built this system in the first place 🤔

Why Q&A Systems for Nature-based Solutions?

World Resources Institute (WRI) seeks to understand how nature-based solutions (NbS) like forest and landscape restoration can minimize the impacts of climate change on local communities.

Nature-based Solutions (NbS) are a powerful ally to address societal challenges, such as climate change, biodiversity loss, and food security. As the world strives to emerge from the current pandemic and move towards the UN Sustainable Development Goals, it is imperative that future investments in nature reach their potential by contributing to the health and well-being of people and the planet.

Read more | source: medium.com

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Using an NLP Q&A System To Study Climate Hazards and Nature-Based Solutions