Abstract: In some examples, natural language processing (NLP) and artificial intelligence based searching may include identifying named entities in text from a corpus of documents. References in the text may be resolved with the identified named entities. Links between the named entities may be determined, and a bi-direction rootless graph may be generated. Semantic relationships may be determined from text of the named entities, and blacklist keywords may be identified. Machine learning classification may be performed based on a pair of the named entities and a blacklist keyword. A classification may be determined based on the pair of named entities and the blacklist keyword, and a rule may be identified that specifies which named entity in the pair is to be flagged. Further, a node in the graph may be flagged based on an association with the named entity identified according to the rule.

Abstract: In some examples, natural language processing (NLP) and artificial intelligence based searching may include identifying named entities in text from a corpus of documents. References in the text may be resolved with the identified named entities. Links between the named entities may be determined, and a bi-direction rootless graph may be generated. Semantic relationships may be determined from text of the named entities, and blacklist keywords may be identified. Machine learning classification may be performed based on a pair of the named entities and a blacklist keyword. A classification may be determined based on the pair of named entities and the blacklist keyword, and a rule may be identified that specifies which named entity in the pair is to be flagged. Further, a node in the graph may be flagged based on an association with the named entity identified according to the rule.