Stanford CoreNLP is an extensible annotation-based NLP pipeline that provides core natural language analysis. This open source toolkit is quite widely used, both in the research NLP community and also among commercial and government users of open source NLP technology.
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 dates, times, and numeric quantities, and mark up the structure of sentences in terms of phrases and word dependencies, and indicate which noun phrases refer to the same entities.
Stanford CoreNLP integrates many NLP tools, including the part-of-speech (POS) tagger, the named entity recognizer (NER), the parser, the coreference resolution system, the sentiment analysis, and the bootstrapped pattern learning tools. The basic distribution provides model files for the analysis of English, but the engine is compatible with models for other languages.
Stanford CoreNLP is written in Java.
- Part-of-speech tagging.
- Named entity recognition.
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