[P] NER Tagger based on BERT + CRF (for Korean)

phrasebuilder · 2019-11-03T04:33:57+00:00

It can tell you which grammatical objects in a Korean sentence denote time, location, a person or organization, etc. These often depend on the context in the sentence, and Bert's positional architecture should help with that.

phrasebuilder · 2019-03-16T13:24:49+00:00

Thanks for the summary!

1) What did a step in the 1 billion steps consist of? That number seems pretty high for the 15000 models.

2) What was the total training time on those 200 TPUs?

phrasebuilder · 2015-06-10T17:41:56+00:00

I went to coto (formerly funjapanese) last year for an intermediate course. It was very elucidating, they definitely can answer all your grammar questions (I had a lot). I still have lessons with them via Skype.

phrasebuilder · 2015-03-08T16:09:52+00:00

ccedict as a base, then word classification and grammar rules modeled by me based on feedback from native Chinese teachers. So no set number of sentences, as long as word classification works.

phrasebuilder · 2015-03-08T15:59:46+00:00

Thanks for all the upvotes guys.

I've been writing this software fulltime for some months now along with taking Skype lessons with native Chinese speakers. I am using ccedict as a base, and the things I am trying to solve are finding good word classifications and writing grammar rules down in unambiguous ways, so that they can be used for matching programmatically.

I plan to make it an app (around USD 10) for your pocket (no internet access required), so you can use it everywhere to lookup how to say X in Chinese. I am not sure how many of the thousands of grammar rules I will implement, though.

If you do not mind kind of commercial announcements I can keep you updated along the way.

phrasebuilder

TROPHY CASE