Triple

T17339980
Position Surface form Disambiguated ID Type / Status
Subject Avco E421040 entity
Predicate successor P78 FINISHED
Object Textron NE ONNED1

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: Textron | Statement: [Avco, successor, Textron]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Textron
Context triple: [Avco, successor, Textron]
  • A. Textron chosen
    Textron is a diversified American industrial conglomerate best known for its aerospace, defense, and industrial products, including brands like Bell, Cessna, and Beechcraft.
  • B. Bell Textron
    Bell Textron is a major American aerospace manufacturer best known for designing and producing helicopters and tiltrotor aircraft for both military and commercial use.
  • C. Textron Aviation
    Textron Aviation is a major American aircraft manufacturer known for producing Cessna and Beechcraft airplanes for business, general aviation, and special mission use.
  • D. Textron Systems
    Textron Systems is a U.S.-based defense and aerospace technology company that develops and manufactures advanced military systems, unmanned platforms, and related solutions.
  • E. Spirit AeroSystems
    Spirit AeroSystems is one of the world’s largest non-OEM designers and manufacturers of aerostructures for commercial and defense aircraft.
  • 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_69d889d3adc881909319f1edb8d2a956 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43a14ec90819098db2ac0d58a53e1 completed April 19, 2026, 2:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a019552a0208190bd8bd0f9588911c3 in_progress May 11, 2026, 8:37 a.m.
Created at: April 10, 2026, 5:44 a.m.