Ma-Dan/XLNet-ChineseNER
Tensorflow solution of NER task Using BiLSTM-CRF model with CMU/Google XLNet
This tool helps identify and extract specific entities like organization names, personal names, and locations from Chinese text. You provide raw Chinese text, and it returns the same text with these key entities clearly marked. This is most useful for data analysts, researchers, or anyone working with large volumes of Chinese-language content who needs to quickly pinpoint crucial information.
No commits in the last 6 months.
Use this if you regularly process Chinese text and need to automatically extract organization names, people's names, and geographic locations for analysis or indexing.
Not ideal if you need to identify a wide variety of entity types beyond names and locations, or if your text is not in Chinese.
Stars
45
Forks
6
Language
Python
License
—
Category
Last pushed
Oct 23, 2019
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/Ma-Dan/XLNet-ChineseNER"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
hellohaptik/chatbot_ner
chatbot_ner: Named Entity Recognition for chatbots.
openeventdata/mordecai
Full text geoparsing as a Python library
Rostlab/nalaf
NLP framework in python for entity recognition and relationship extraction
mpuig/spacy-lookup
Named Entity Recognition based on dictionaries
NorskRegnesentral/skweak
skweak: A software toolkit for weak supervision applied to NLP tasks