한글 NER 테스트 (BI-LSTM CRF , Attention Seq2Seq)

• glove vector lib download needed.
  . locate txt file under data/glove.6B/
• glove vector Data file (download)

wget http://nlp.stanford.edu/data/glove.6B.zip

• step1 : make it work on python3.5 and tf1.1 (done)
• step2 : test korean with mecab tockenizer (done)
• step3 : develop whole process on hoyai project with rest webservice
  . API Client jupyter code here
  . reset server github link
  . start service with docker
  

Blog explaining Theory

Check original projects blog post

Functions implemented for Korean NER

• Simple WebCrawler : gather data from korean wiki pedia for w2v train
• w2v, fasttext embedding model : provide custom train for model
• korean char divide func : divide Korean char into smaller pieces for train
• BI-LSTM CRF for NER : implement it with tensorflow
• Attention seq2seq for NER : working on it (~ing)

Korean NER Test Result

• Train Data Example: link
  . you have to preprocess data first before use it
• Word Level Test

['한화증권']['OG']
['김승우']['PS']
['김수상']['PS']
['6시30분']['DT']

• Sentence Level Test

[['6시30분']['한화건설']['김승우']['약속']]
[['DT']['OG']['PS']['OO']]