stanford-ner ☆
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Description:
Stanford NLP Group's implementation of a Named Entity Recognizer
Type: Formula  |  Tracked Since: Dec 28, 2025
Links: Homepage  |  formulae.brew.sh
Category: Ai ml
Tags: nlp naturallanguageprocessing ner machinelearning java
Install: brew install stanford-ner
About:
Stanford NER is a Java implementation of a Named Entity Recognizer using Conditional Random Fields (CRF). It identifies and classifies proper nouns like person, organization, and location names within text. The tool provides robust, pre-trained models for high accuracy in natural language processing pipelines.
Key Features:
  • Pre-trained models for Person, Organization, and Location recognition
  • Support for custom model training with annotated data
  • Provides a server mode for high-throughput processing
  • Includes advanced NLP features like part-of-speech tagging and parsing
Use Cases:
  • Extracting entities from news articles or legal documents for data analysis
  • Anonymizing sensitive personal information in datasets
  • Building knowledge graphs by identifying key entities in unstructured text
Alternatives:
  • spaCy – Python-based, generally faster for inference but Stanford NER offers highly accurate, industry-standard CRF models.
  • NLTK – Python library offering NER capabilities, often used for educational purposes or lighter-weight tasks.
Version History
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