Triple

T9677934
Position Surface form Disambiguated ID Type / Status
Subject Steve Miller E234206 entity
Predicate notableWork P4 FINISHED
Object Jet Airliner
"Jet Airliner" is a popular rock song by the Steve Miller Band, best known for its catchy chorus and frequent radio play since the late 1970s.
 E813840 NE FINISHED

How this triple was built (4 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: Jet Airliner | Statement: [Steve Miller, notableWork, Jet Airliner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jet Airliner
Context triple: [Steve Miller, notableWork, Jet Airliner]
  • A. Boeing 747
    The Boeing 747 is a wide-body, long-range commercial airliner famous for its distinctive hump-backed upper deck and for revolutionizing mass international air travel as one of the first jumbo jets.
  • B. Learjet
    Learjet is an American manufacturer renowned for its pioneering line of small, fast business jets that helped define the modern private jet industry.
  • C. Avion
    Avion is a commune in the Pas-de-Calais department in northern France.
  • D. Aeroplan
    Aeroplan is Air Canada's loyalty program that allows members to earn and redeem points for flights, upgrades, and other travel-related rewards.
  • E. Beechcraft King Air
    The Beechcraft King Air is a family of twin-turboprop utility aircraft widely used around the world for military, government, and civilian transport, training, and special-mission roles.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Jet Airliner
Triple: [Steve Miller, notableWork, Jet Airliner]
Generated description
"Jet Airliner" is a popular rock song by the Steve Miller Band, best known for its catchy chorus and frequent radio play since the late 1970s.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jet Airliner
Target entity description: "Jet Airliner" is a popular rock song by the Steve Miller Band, best known for its catchy chorus and frequent radio play since the late 1970s.
  • A. Boeing 747
    The Boeing 747 is a wide-body, long-range commercial airliner famous for its distinctive hump-backed upper deck and for revolutionizing mass international air travel as one of the first jumbo jets.
  • B. Learjet
    Learjet is an American manufacturer renowned for its pioneering line of small, fast business jets that helped define the modern private jet industry.
  • C. Avion
    Avion is a commune in the Pas-de-Calais department in northern France.
  • D. Aeroplan
    Aeroplan is Air Canada's loyalty program that allows members to earn and redeem points for flights, upgrades, and other travel-related rewards.
  • E. Beechcraft King Air
    The Beechcraft King Air is a family of twin-turboprop utility aircraft widely used around the world for military, government, and civilian transport, training, and special-mission roles.
  • F. None of above. chosen

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_69ca84c99e34819092e5563a7106cfca completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9c9b01708190aaf51cf4d36015a0 completed April 1, 2026, 10:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69d18a34adec8190a4a260d029e408aa completed April 4, 2026, 10:01 p.m.
NEDg Description generation batch_69d18aa1e9a48190bf26da5482fd0770 completed April 4, 2026, 10:03 p.m.
NED2 Entity disambiguation (via description) batch_69d18b6a2fb0819092ee274310721b50 completed April 4, 2026, 10:06 p.m.
Created at: March 30, 2026, 8:16 p.m.