Triple

T2603890
Position Surface form Disambiguated ID Type / Status
Subject EXS E58609 entity
Predicate airlineFleetType P1524 FINISHED
Object Boeing 737 E22402 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 737 | Statement: [EXS, airlineFleetType, Boeing 737]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Boeing 737
Context triple: [EXS, airlineFleetType, Boeing 737]
  • A. Boeing 737 chosen
    The Boeing 737 is a widely used narrow-body commercial jet airliner known for being one of the best-selling passenger aircraft in aviation history.
  • B. Boeing 757
    The Boeing 757 is a mid-size, narrow-body twin-engine jet airliner widely used for short- to medium- and some long-haul routes, known for its strong performance and versatility.
  • C. Boeing 777
    The Boeing 777 is a long-range, wide-body twin-engine jet airliner widely used by airlines around the world for international passenger flights.
  • D. Boeing 767
    The Boeing 767 is a wide-body, twin-engine jet airliner widely used for medium- to long-haul commercial flights and cargo operations.
  • E. Boeing 727
    The Boeing 727 is a mid-sized, three-engine narrow-body jet airliner introduced in the 1960s that became one of the most widely used commercial aircraft for short- and medium-haul routes.
  • 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_69ab4ac3523881909679750c9f8c2dec completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abdd1ca0248190aa15f80b2798524e completed March 7, 2026, 8:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69b1de7ea6b48190a992ef2c4b3d7c42 completed March 11, 2026, 9:28 p.m.
Created at: March 6, 2026, 9:49 p.m.