DA-southampton/ner
命名体识别(NER)综述-论文-模型-代码(BiLSTM-CRF/BERT-CRF)-竞赛资源总结-随时更新
This resource helps extract key information like names, locations, organizations, or specific terms from text data, which is crucial for tasks like building keyword matching features. It summarizes various techniques and provides code resources, from simpler dictionary-based methods to advanced deep learning models. This is ideal for natural language processing engineers or data scientists who need to identify and categorize specific entities within large volumes of text from various domains like entertainment or finance.
473 stars. No commits in the last 6 months.
Use this if you need to automatically identify and extract important named entities from unstructured text, especially in Chinese, for applications like content categorization or search.
Not ideal if you are looking for a ready-to-use, off-the-shelf software application for named entity recognition without needing to delve into model implementation or code.
Stars
473
Forks
49
Language
—
License
—
Category
Last pushed
Jun 15, 2020
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/DA-southampton/ner"
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