What is CoreNLP?
It provides a set of natural language analysis tools written in Java. It can take raw human language text input and give the base forms of words, their parts of speech, whether they are names of companies, people, etc., normalize and interpret dates, times, and numeric quantities, mark up the structure of sentences in terms of phrases or word dependencies, and indicate which noun phrases refer to the same entities.
CoreNLP is a tool in the Voice & Audio Models category of a tech stack.
Key Features
An integrated NLP toolkit with a broad range of grammatical analysis toolsA fast, robust annotator for arbitrary texts, widely used in productionA modern, regularly updated package, with the overall highest quality text analyticsSupport for a number of major (human) languagesAvailable APIs for most major modern programming languages
Ability to run as a simple web service
CoreNLP Pros & Cons
Pros of CoreNLP
No pros listed yet.
Cons of CoreNLP
No cons listed yet.
CoreNLP Alternatives & Comparisons
What are some alternatives to CoreNLP?
Transformers
It provides general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet…) for Natural Language Understanding (NLU) and Natural Language Generation (NLG) with over 32+ pretrained models in 100+ languages and deep interoperability between TensorFlow 2.0 and PyTorch.
SpaCy
It is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest research, and was designed from day one to be used in real products. It comes with pre-trained statistical models and word vectors, and currently supports tokenization for 49+ languages.
rasa NLU
rasa NLU (Natural Language Understanding) is a tool for intent classification and entity extraction. You can think of rasa NLU as a set of high level APIs for building your own language parser using existing NLP and ML libraries.
