Triple

T26673985
Position Surface form Disambiguated ID Type / Status
Subject 12th Flying Training Wing E672408 entity
Predicate aircraftOperated P1523 FINISHED
Object T-51 Mustang
The T-51 Mustang is a light, kit-built replica of the World War II-era P-51 Mustang fighter, used primarily for sport and training purposes.
 E1749363 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: T-51 Mustang | Statement: [12th Flying Training Wing, aircraftOperated, T-51 Mustang]
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: T-51 Mustang
Triple: [12th Flying Training Wing, aircraftOperated, T-51 Mustang]
Generated description
The T-51 Mustang is a light, kit-built replica of the World War II-era P-51 Mustang fighter, used primarily for sport and training purposes.

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_69eecda00a9c8190b2691f4d89db03b6 completed April 27, 2026, 2:44 a.m.
NER Named-entity recognition batch_69f61701f5ac8190bda13b38afb6a9b9 completed May 2, 2026, 3:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12297b4de88190be97cd481f406b73 completed May 23, 2026, 10:26 p.m.
NEDg Description generation batch_6a1229dbb2b481908d3473ba35b9ed3d completed May 23, 2026, 10:27 p.m.
NED2 Entity disambiguation (via description) batch_6a122a424f0081908a44e41a19c80a7d completed May 23, 2026, 10:29 p.m.
Created at: April 27, 2026, 3:15 a.m.