Micro Signal █ █158★1484★6999 donor egg IVF surrogacy choose sex of a boy born ██ ██ tube package Surrogacy surrogacy package born boy ██ ███ ██ sex surrogate selected test-tube baby born boy █████ ███ surrogacy IVF surrogacy boy ███ donor egg IVF surrogacy ███
Jiagu natural language processing tools
Jiagu to BiLSTM and other models based on the use of large-scale training corpus is made. We will provide Chinese word segmentation, POS tagging, named entity recognition, sentiment analysis, relationship mapping knowledge extraction, keyword extraction, text summarization, new words commonly found in natural language processing and other functions. Making reference to the advantages and disadvantages of the major tools, we will give you back Jiagu.
table of Contents
Functions provided are:
- Chinese word
- Speech tagging
- Named entity recognition
- Sentiment Analysis (Models in training)
- Knowledge Mapping relation extraction
- Keyword extraction
- Text Summarization
- Discover new words
- and many more. . . .
Mounting
pip install
pip install jiagu
Source Installation
git clone https://github.com/ownthink/Jiagu
cd Jiagu
python3 setup.py install
Use
- Quick Start: word, speech tagging, named entity recognition
jiagu Import
# jiagu.init () # can be initiated manually or dynamically initialize
text = 'Xiamen tomorrow will not rain' words = jiagu.seg (text) # word Print (words) POS = jiagu.pos (words) # speech tagging Print (POS) NER = jiagu.ner (text) # NER print (ner)
- Chinese word
Word use various modes
jiagu Import
text = 'Chinese clothing and clothing'
words = jiagu.seg (text) # default word Print (words) words = jiagu.seg ([text, text, text], the INPUT = 'BATCH') # batch word, speed . Print (words) words = jiagu.seg (text, Model = 'mmseg') # segmentation algorithm using mmseg print (list (words))
Custom word model (will be provided separately msr, pku, cnc standard aliquots word)