Retrieving the Right Information About COVID-19 With Golden Retriever

COVID-19, which spread out of Wuhan, China, to the rest of the world in recent weeks has caused much public concern. During this outbreak, there has been much information and misformation being shared online and offline. Sometimes it is difficult to tell them apart, at least without exercising some due diligence to look up reputable websites.

To help combat misinformation, AI Singapore (AISG) developed an information retrieval application for questions about COVID-19 using its Golden Retriever tool based on information from the Ministry of Education and Ministry of Health FAQ websites (updated as of 10 Feb).

Golden Retriever uses an AI model called a Transformer that is able to understand words in context, as well as to account for synonyms. A traditional approach, like a keyword search, on the other hand, will only be able to locate exact phrases in the document. Instead of hunting for your answer by searching using different keywords, Golden Retriever is able to return a ranked list of answers that best fit a query phrase. This requires a knowledge base that has been divided into individual clauses. Each clause is a discrete piece of text like a paragraph, or an answer to a FAQ. The good thing is that no model training is necessary as it is pre-trained, so it is already able to match questions to the appropriate clause out-of-the-box.

To use Golden Retriever, head to here. Make sure the Knowledge Base selected is “COVID-19”. Type your question into the query box and hit “Fetch”. It is as simple as that!

As with all machine learning tools, the answers are not guaranteed to be always accurate, and should not be used for diagnostic purposes or to make important decisions. For any clarifications on the content delivered, please look to the relevant authority for advice.

Golden Retriever is a Brick (pre-built solutions) from AI Makerspace, a platform offered by AISG to help SMEs and start-ups accelerate the adoption of AI in Singapore.

Related Stories

(Image source)