Google has released Natural Questions, a dataset of 300,000 questions and human annotated answers to advance natural language understanding in computers. The questions come from anonymized Google search queries with both short and long answers sourced from Wikipedia. Along with the training dataset, Google has released a dataset of 16,000 questions where each question has answers from five different annotators to help researchers test their question and answer systems.
Helping AI Answer Real Google Search Queries
Michael McLaughlin is a research analyst at the Center for Data Innovation. He researches and writes about a variety of issues related to information technology and Internet policy, including digital platforms, e-government, and artificial intelligence. Michael graduated from Wake Forest University, where he majored in Communication with Minors in Politics and International Affairs and Journalism. He received his Master’s in Communication at Stanford University, specializing in Data Journalism.
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