Relation Extraction

Identify people, locations, and organizations within a body of text.

Identify who the words “he,” “she,” and “they” are referring to.

Identify relationships between entities.

Categorize any kind of text.

Classify text as positive, negative, or neutral, returned as a classifier.

Identify the topic that the text is talking about without the need for training or ontology.

Summarize a document to meet your needs and identify the key information.

Automatically identify and extract the key information within a document.

See what parts of the text the models are using for your predictions.

Classify text as likely to have been written by a human or a machine.

Identify claims within any text and determine if these claims are supported or refute other claims.

Identify jargon and industry acronyms within the text and link it to an explanation of the terms.

Extract a quote and its author from a body of text.

Generate a human-quality title or headline for a body of text.

Answer specific questions about a body of text.

Classify a piece of text as being related to Diplomacy, Information Operations, Military, International Economics, Illicit Finance, Intelligence, and Law Enforcement.

Identify all the locations in a piece of text and connect them to a map.

Link extracted entities with your knowledge graph or Primer’s knowledge base.

Move beyond people, places, and organizations and identify other entities.

Determine the difference between two pieces of text or two versions.

Identify the real world events within any piece of text.

Connect events to form a timeline across your set of documents.