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Warning Super Nerd mode
Alright I've been doing these small weekend projects every now and then to expand my skillset, when I came across this for rudimentary A.I. level parsing (God forbid anyone wasting time spinning content realizes what Google is slowly becoming capable of): Google's open sourcing their "Parsey McParseface" - an english language parser.
Get started here: https://github.com/tensorflow/models/tree/master/syntaxnet
I'm going to go crazy with Syntactic Ngrams of over 350 billion words from the 3.5 million English Language books in Google Books with this and see the outcome: http://commondatastorage.googleapis.com/books/syntactic-ngrams/index.html
More Sauce: http://research.google.com/research-outreach.html#/research-outreach/research-datasets
I'll continue exploring this language parsing since I've got a couple of ideas that have been sitting on the back burner I can use this for. I'll report back if anything comes of these small experiments, maybe another SAAS, who knows.
A bit more about Parsey McParseface: Has Google's Parsey McParseface just solved one of the world's biggest language problems?
Alright I've been doing these small weekend projects every now and then to expand my skillset, when I came across this for rudimentary A.I. level parsing (God forbid anyone wasting time spinning content realizes what Google is slowly becoming capable of): Google's open sourcing their "Parsey McParseface" - an english language parser.
Parsey McParseface recovers individual dependencies between words with over 94% accuracy, beating our own previous state-of-the-art results, which were already better than any previous approach. While there are no explicit studies in the literature about human performance, we know from our in-house annotation projects that linguists trained for this task agree in 96-97% of the cases.
Sauce: Announcing SyntaxNet: The World’s Most Accurate Parser Goes Open Source
Sauce: Announcing SyntaxNet: The World’s Most Accurate Parser Goes Open Source
Get started here: https://github.com/tensorflow/models/tree/master/syntaxnet
I'm going to go crazy with Syntactic Ngrams of over 350 billion words from the 3.5 million English Language books in Google Books with this and see the outcome: http://commondatastorage.googleapis.com/books/syntactic-ngrams/index.html
More Sauce: http://research.google.com/research-outreach.html#/research-outreach/research-datasets
I'll continue exploring this language parsing since I've got a couple of ideas that have been sitting on the back burner I can use this for. I'll report back if anything comes of these small experiments, maybe another SAAS, who knows.
A bit more about Parsey McParseface: Has Google's Parsey McParseface just solved one of the world's biggest language problems?