Triple

T29045896
Position Surface form Disambiguated ID Type / Status
Subject Safran Arrano E735134 entity
Predicate family P566 FINISHED
Object Arrano engine family
The Arrano engine family is a series of modern turboshaft engines developed by Safran Helicopter Engines for new-generation medium helicopters, emphasizing fuel efficiency, reduced emissions, and advanced digital control.
E1847185 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: Arrano engine family | Statement: [Safran Arrano, family, Arrano engine family]
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: Arrano engine family
Triple: [Safran Arrano, family, Arrano engine family]
Generated description
The Arrano engine family is a series of modern turboshaft engines developed by Safran Helicopter Engines for new-generation medium helicopters, emphasizing fuel efficiency, reduced emissions, and advanced digital control.

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_69f077e64b88819094d37bdbca8191b3 completed April 28, 2026, 9:03 a.m.
NER Named-entity recognition batch_69f6606204508190afe4f34752bb682a completed May 2, 2026, 8:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a251f738e00819092cb24795dd594d1 completed June 7, 2026, 7:36 a.m.
NEDg Description generation batch_6a252349bdcc8190a167f8376cf6c58f completed June 7, 2026, 7:52 a.m.
NED2 Entity disambiguation (via description) batch_6a2527fa35c481909dcfac5d18038aed completed June 7, 2026, 8:12 a.m.
Created at: April 28, 2026, 10:05 a.m.