2,210 karma · joined September 5, 2013
I'd love to see somebody taking over and resuscitate it! One interesting direction could be to remove Java dependencies (mostly to Date) so that it's usable in ClojureScript. It would make a great JS library.
(Very small correction: Duckling is rule-based but uses a super simple Naive Bayes classifier to prioritize between the many potential parses produced by the rules -- we see it as a hybrid approach)
Duckling is relevant to parse very structured language, typically temporal expressions (dates and times...). It relies on a mix of rules and machine learning. Rules and datasets for many (human) languages are available in the repo. You don't need a lot of data to add support for what you need, owing to this hybrid rules+ML approach (as opposed to just ML).
I admire the PR stunt.
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your Content and any other content that is or may be developed by Snap1. Get a few thousands book titles that are "long enough" so that the probability they appear in a sentence without meaning the book is low
2. Search these spans in HN comments and use this corpus to train Stanford's CoreNLP NER
3. Run the NER on all comments
4. Check on Openlibrary or another book DB that the extracted spans are real books titles
Thanks for your interesting comments!
That's so outrageous.
Well, it all depends on your definition of true intelligence...
2. We use a combination of traditional NLP (CRF NER, maxent classifiers) and deep learning. The "old" stuff needs less data to be trained. We'll continue to support duckling, we always love PRs, please help us!
Use cases on Messenger will probably be more around customer care or entertainment, news, etc.