Triple

T35017505
Position Surface form Disambiguated ID Type / Status
Subject Mi-22 E1010091 entity
Predicate originatingIndustry P158848 FINISHED
Object Soviet aerospace industry
The Soviet aerospace industry was the state-controlled sector responsible for designing and producing the USSR’s aircraft, helicopters, missiles, and spacecraft, making it one of the world’s leading aerospace powers during the Cold War.
E2123233 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: Soviet aerospace industry | Statement: [Mi-22, originatingIndustry, Soviet aerospace industry]
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: Soviet aerospace industry
Triple: [Mi-22, originatingIndustry, Soviet aerospace industry]
Generated description
The Soviet aerospace industry was the state-controlled sector responsible for designing and producing the USSR’s aircraft, helicopters, missiles, and spacecraft, making it one of the world’s leading aerospace powers during the Cold 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_69f76dcc3ac8819096a3ed52f5fa2523 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_6a01602b294081908fcced9fef430b0c completed May 11, 2026, 4:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a37bd1d97c0819080f01cf6964bcca5 completed June 21, 2026, 10:29 a.m.
NEDg Description generation batch_6a37bdd99244819093669c98be46f903 completed June 21, 2026, 10:32 a.m.
NED2 Entity disambiguation (via description) batch_6a37bfd6e5a48190b6bcc0b9860ad4bb completed June 21, 2026, 10:41 a.m.
Created at: May 3, 2026, 4:01 p.m.