Triple

T18922176
Position Surface form Disambiguated ID Type / Status
Subject Bell Rocket Belt E462884 entity
Predicate manufacturer P490 FINISHED
Object Bell Aerosystems NE NERFINISHED

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: Bell Aerosystems | Statement: [Bell Rocket Belt, manufacturer, Bell Aerosystems]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bell Aerosystems
Context triple: [Bell Rocket Belt, manufacturer, Bell Aerosystems]
  • A. Bell Aircraft chosen
    Bell Aircraft was an American aerospace manufacturer best known for pioneering experimental and military aircraft, including the first supersonic research plane.
  • B. Fairchild Aircraft
    Fairchild Aircraft was an American aerospace company known for producing military and civilian aircraft, including notable transport and trainer planes throughout the mid-20th century.
  • C. Folland Aircraft
    Folland Aircraft was a British aircraft manufacturer best known for producing light fighter and trainer aircraft in the post-World War II era.
  • D. Swearingen Aircraft
    Swearingen Aircraft was an American aircraft manufacturer best known for producing small commuter and business aircraft, including the Metroliner series.
  • E. Beechcraft
    Beechcraft is an American aircraft manufacturer known for producing a wide range of civil and military airplanes, including popular training, business, and utility aircraft.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8dcfdbbb881909964fa5a75bd0b48 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5c9b4822c8190a0aeceb4499e775e completed April 20, 2026, 6:37 a.m.
Created at: April 10, 2026, 11:59 a.m.