Systems for understanding human language have advanced significantly in the last few years, as researchers have improved approaches to artificial intelligence like deep learning. These methods set algorithms crawling through immense troves of data to draw connections between words and phrases. This is called “parsing,” or identifying each word and it’s role in the sentence.
Today Google is publishing the code for its language system called SyntaxNet, as well as an already-trained program for English called Parsey McParseface. Google’s tests put Parsey McParseface’s accuracy for correctly understanding words at more than 94 percent—close to Google’s internal benchmarks of 96 percent for the humans they employ for the same task. With SyntaxNet, researchers outside of Google will be able to train and implement their own language understanding systems for other languages, or try to beat Google’s score.
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