- Add the new tutorial to the document (train a model for Japanese NER). - Add load_file function to nagisa.utils. - Fix 'single_word_list' compiler in nagisa.Tagger and support word segmentation using a regular expression.
0.2.3
- FIx 11 . By separating tagging into word segmentation and POS tagging in tagger.py, `nagisa.tagging` reduces wasteful memory and improves the speed in word segmentation. - Fix typo in README.md
0.2.2
- Update the document (e.g, add train a model for Japanese Universal Dependencies). - Fix log output of nagisa.fit function. - Fix issues from Codacy (e.g, delete unused codes in train.py). - Add appveyor.yml for Windows users.
0.2.0
- Provide a simple train method for a joint word segmentation and sequence labeling (e.g, POS-tagging, NER) model. - Fix ZeroDivisionError in mecab_system_eval.py.
0.1.2
- Provide the postagging method 8 - Adopt the longest match to extract a word in `nagisa.Tagger(single_word_list)`