Triple

T29742821
Position Surface form Disambiguated ID Type / Status
Subject Robbie Risner E752659 entity
Predicate fullName P16 FINISHED
Object James Robinson Risner
James Robinson Risner was a highly decorated United States Air Force fighter pilot and brigadier general renowned for his heroism in the Korean and Vietnam Wars, including enduring years as a prisoner of war.
E1885441 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: James Robinson Risner | Statement: [Robbie Risner, fullName, James Robinson Risner]
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: James Robinson Risner
Triple: [Robbie Risner, fullName, James Robinson Risner]
Generated description
James Robinson Risner was a highly decorated United States Air Force fighter pilot and brigadier general renowned for his heroism in the Korean and Vietnam Wars, including enduring years as a prisoner of war.

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_69f0d62b064081908c1ae61cd68fb139 completed April 28, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f673645c888190bdffeb6448487ec4 completed May 2, 2026, 9:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26e5e24eb08190934ef78347a317c8 completed June 8, 2026, 3:55 p.m.
NEDg Description generation batch_6a26e68b913481908d53ac147ad34f74 completed June 8, 2026, 3:58 p.m.
NED2 Entity disambiguation (via description) batch_6a26e7057a0c819089535980d5b98484 completed June 8, 2026, 4 p.m.
Created at: April 28, 2026, 7:49 p.m.