Triple

T10739322
Position Surface form Disambiguated ID Type / Status
Subject LX E253278 entity
Predicate airlineFleetType P1524 FINISHED
Object Boeing 777-300ER E23610 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: Boeing 777-300ER | Statement: [LX, airlineFleetType, Boeing 777-300ER]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Boeing 777-300ER
Context triple: [LX, airlineFleetType, Boeing 777-300ER]
  • A. Boeing 777 chosen
    The Boeing 777 is a long-range, wide-body twin-engine jet airliner widely used by airlines around the world for international passenger flights.
  • B. Boeing 737-900ER
    The Boeing 737-900ER is an extended-range variant of the 737-900, designed as a high-capacity, single-aisle jetliner for medium-haul commercial flights.
  • C. Boeing 737-800
    The Boeing 737-800 is a widely used narrow-body commercial jet airliner known for short- to medium-haul flights and high fuel efficiency within the 737 Next Generation family.
  • D. Boeing 777X
    The Boeing 777X is Boeing’s latest generation long-range, wide-body twin-engine jet airliner, featuring new composite wings with folding wingtips and upgraded engines for improved efficiency and capacity.
  • E. Airbus A330
    The Airbus A330 is a wide-body, twin-engine jet airliner designed for medium- to long-haul routes and widely used by airlines around the world.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d6aa5e51e8819095f06881cecf152e completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d710424d8c81908ee9b59d622f2af5 completed April 9, 2026, 2:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69de558f26e88190a9cb8f4d0539e5a5 completed April 14, 2026, 2:56 p.m.
Created at: April 8, 2026, 9:14 p.m.