Triple

T25980002
Position Surface form Disambiguated ID Type / Status
Subject Old Right (United States) E646040 entity
Predicate associatedWith P37 FINISHED
Object Garet Garrett
Garet Garrett was an American journalist, novelist, and staunch non-interventionist critic of the New Deal whose writings became influential within the Old Right movement.
E1703116 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Garet Garrett | Statement: [Old Right (United States), associatedWith, Garet Garrett]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Garet Garrett
Triple: [Old Right (United States), associatedWith, Garet Garrett]
Generated description
Garet Garrett was an American journalist, novelist, and staunch non-interventionist critic of the New Deal whose writings became influential within the Old Right movement.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69e77e881fc08190ba1c8dc7e2a07f97 completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f6050e507881909e3bc0c33e8a8c7e completed May 2, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11078dd2dc8190b4b36697dfd4680b completed May 23, 2026, 1:49 a.m.
NEDg Description generation batch_6a11085043a08190b86f770075f609c1 completed May 23, 2026, 1:52 a.m.
NED2 Entity disambiguation (via description) batch_6a110925bec881908c0bdb63355e4e31 completed May 23, 2026, 1:55 a.m.
Created at: April 22, 2026, 8:54 a.m.