returned for Tags:"NER"
Stanford CoreNLP provides a set of natural language analysis tools which can take raw English 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...
Stanford NER (also known as CRFClassifier) is a Java implementation of a Named Entity Recognizer. Named Entity Recognition (NER) labels sequences of words in a text which are the names of things, such as person and company names, or gene and protein names. The software provides a general (arbitrary...
The Apache OpenNLP library is a machine learning based toolkit for the processing of natural language text. It supports the most common NLP tasks, such as tokenization, sentence segmentation, part-of-speech tagging, named entity extraction, chunking, parsing, and coreference resolution. These tasks...
Provides a way to parse html or csv tagged corpuses and get confusion matrix from corpuses comparison. For more information https://github.com/dmit25/DZ.Tools
This package is a wrapper for DBPedia Spotlight
Resource package that contains named-entity recognition for SimpleNetNlp project (simple C# wrapper for Stanford CoreNLP).
Botsharp.NLP is a set of tools for building C# programs to work with human language data. It can be used in common tasks like POS, NER and text classification in the NLP or NLU field.
BotSharp.NLP has implemented below machine learning algorithms:
Conditional Random Field (CRF)
Natural language query parser and rule-based named entity recognizer.
NLQuery: natural language query parser recognizes entities in context of structured sources: tabular data (database, indexed data). Can be used for building natural language interface to SQL database or OLAP cube, implementing custom search engine.