An Upgrade to SyntaxNet, New Models and a Parsing Competition
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An Upgrade to SyntaxNet, New Models and a Parsing Competition
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Re: An Upgrade to SyntaxNet, New Models and a Parsing Competition
#2Very interesting release.
The bit about guessing the part of speech, stem, etc. for previously unseen words should (I think) make it much more useful in contexts that succumb to neologizing, verbing nouns, nouning verbs, and so on (such as business writing, technical writing, academic papers, science fiction & fantasy, slang, etc.).
I wonder how well it would do at parsing something that seems deliberately impenetrable, like TimeCube rants, or postmodern literary criticism.
Re: An Upgrade to SyntaxNet, New Models and a Parsing Competition
#3This looks amazing. I'm especially curious how well it will work at identifying Gene/chemical nomenclature since it is fairly consistent like English spelling. For named entity recognition in biomedical text this could be really useful!
Re: An Upgrade to SyntaxNet, New Models and a Parsing Competition
#4Given how many areas NLP can be applied to, I can only imagine all of these future internal project proposals where someone has to explain to some C-suite exec how they are going to revolutionize the business with Parsey McParseface. Or better yet, when they have to budget a big upgrade to the "DRAGNN based ParseySaurus". Fun times ahead.
Re: An Upgrade to SyntaxNet, New Models and a Parsing Competition
#5See also: spaCy, which is an open-source NLP framework that has some integration with Keras as well: https://news.ycombinator.com/item?id=13874787
...and apparently will release a major version update today. Ouch.
Re: An Upgrade to SyntaxNet, New Models and a Parsing Competition
#6Hoping this will quickly make into someone's home grown self-hosted version of Alexa.
Alexa, turn the lights on in the kitchen.
Alexa, turn on the kitchen light.
Alexa, light up the kitchen.
Should all accomplish the same task using this framework.
Re: An Upgrade to SyntaxNet, New Models and a Parsing Competition
#7See also: spaCy, which is an open-source NLP framework that has some integration with Keras as well: https://news.ycombinator.com/item?id=13874787 ...and apparently will release a major version update today . Ouch.
I don't think spaCy will be hurting any time soon. When SyntaxNet was first released last year, Matthew Honnibal had a good writeup [0] of how spaCy vastly outperforms with speed while keeping reasonable accuracy:
>On the time-honoured benchmark for this task, Parsey McParseface achieves over 94% accuracy, at around 600 words per second. On the same task, spaCy achieves 92.4%, at around 15,000 words per second. The extra accuracy might not sound like much, but for applications, it's likely to be pretty significant.
If spaCy is able to increment the accuracy and maintain the large performance gap, it'll still be my go-to NLP framework!
Re: An Upgrade to SyntaxNet, New Models and a Parsing Competition
#8Hoping this will quickly make into someone's home grown self-hosted version of Alexa. Alexa, turn the lights on in the kitchen. Alexa, turn on the kitchen light. Alexa, light up the kitchen. Should all accomplish the same task using this framework.
I see your point, but the tasks that you have listed (and more difficult variants) can be easily handled using rule-based systems.
Re: An Upgrade to SyntaxNet, New Models and a Parsing Competition
#9Given how many areas NLP can be applied to, I can only imagine all of these future internal project proposals where someone has to explain to some C-suite exec how they are going to revolutionize the business with Parsey McParseface. Or better yet, when they have to budget a big upgrade to the "DRAGNN based ParseySaurus". Fun times ahead.
there's probably a cooler internal name for it.
Re: An Upgrade to SyntaxNet, New Models and a Parsing Competition
#10Hoping this will quickly make into someone's home grown self-hosted version of Alexa. Alexa, turn the lights on in the kitchen. Alexa, turn on the kitchen light. Alexa, light up the kitchen. Should all accomplish the same task using this framework.
> Alexa, light up the kitchen
May also be interpreted as:
Alexa, set fire to the kitchen