The service provides analysis of selected text passages to identify named entities and statements of fact with disambiguation to distinguish similar text strings. It applies machine learning algorithms and natural language processing to connect a text sample with a knowledge base and identify known elements and their relationships.
API methods support submission of a text sample to be parsed. Methods identify text strings associated with known named entities and detail the relationships and dependencies between them by type. Methods also identify synonyms for identified terms and topics or themes referenced in the text sample.
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The TextRazor PHP Sample Code by TextRazor demonstrates how to define categories and upload them as a new classifier, test the classifier out with an analysis request, and define a new dictionary to add new entries.