Bing can now answer queries with a simple ‘Yes’ or ‘No’

The yes/no summary uses natural-language modeling and comes with a carousel of sources.

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Bing can now return a “Yes” or “No” answer for certain queries, the company announced Tuesday. The new search feature includes the one-word answer as well as a carousel of related excerpts from various sources.

What it looks like. This was the top result for the query “can dogs eat chocolate” prior to the change.

Bing Yes No Before 1
Source: Bing.

The new yes/no summary result now looks like this:

Bing Yes No After

Certain queries will also trigger an option to refine the search for a more specific answer, as seen above. Clicking on one of the refined search options takes you to the results for that query, which may also display the yes/no summary. This feature is currently live in the U.S. and will eventually expand to more markets.

How it works. In the example above, Natural Language Representation (NLR) modeling enables Bing to infer that “chocolate is toxic to dogs” means dogs cannot eat chocolate, despite sources not explicitly stating so.

To create this feature, Bing began with a pre-trained language model that it adjusted to perform two separate, complementary tasks: assessing the relevance of document passages in relation to the search query, and providing a definitive “Yes” or “No” answer by ingesting and summarizing multiple sources.

Why we care. This new search feature provides users with a concise answer as well as a number of sources highlighted in the accompanying carousel. Webmasters and SEOs should keep track of the keywords they’re currently ranking for that trigger this feature, and monitor how their impressions and traffic shift with the change.


Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.


About the author

George Nguyen
Contributor
George Nguyen is the Director of SEO Editorial at Wix, where he manages the Wix SEO Learning Hub. His career is focused on disseminating best practices and reducing misinformation in search. George formerly served as an editor for Search Engine Land, covering organic and paid search.

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