Google Play icon

Google QUEST Q&A Labeling

Share
Posted November 26, 2019

Computers are really good at answering questions with single, verifiable answers. But, Humans are better at addressing subjective questions that require a deeper, multidimensional understanding of context – something computers aren’t trained to do well. Questions can take many forms – some have multi-sentence elaborations, others may be simple curiosity or a fully developed problem.

Image credit: Mohammed Hassan via Pxhere, CC0 Public Domain

Image credit: Mohammed Hassan via Pxhere, CC0 Public Domain

Unfortunately, it’s hard to build better subjective question-answering algorithms because of a lack of data and predictive models. That’s why the CrowdSource team at Google Research, a group dedicated to advancing NLP and other types of ML science via crowdsourcing, has collected data on a number of these quality scoring aspects.

The Competitor uses this new dataset to build predictive algorithms for different subjective aspects of question-answering. The question-answer pairs were gathered from nearly 70 different websites, in a “common-sense” fashion.

Submission to this Challenge must be received by 11:59 PM UTC February 3, 2020.

Source: Kaggle

Featured news from related categories:

Technology Org App
Google Play icon
87,029 science & technology articles

Most Popular Articles

  1. You Might Not Need a Hybrid Car If This Invention Works (January 11, 2020)
  2. Toyota Raize a new cool compact SUV that we will not see in this part of the world (November 24, 2019)
  3. An 18 carat gold nugget made of plastic (January 13, 2020)
  4. Human body temperature has decreased in United States, study finds (January 10, 2020)
  5. Donkeys actually prefer living in hot climate zones (January 6, 2020)

Follow us

Facebook   Twitter   Pinterest   Tumblr   RSS   Newsletter via Email