Triple

T20722647
Position Surface form Disambiguated ID Type / Status
Subject Folland Midge E509356 entity
Predicate manufacturer P490 FINISHED
Object Folland Aircraft 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: Folland Aircraft | Statement: [Folland Midge, manufacturer, Folland Aircraft]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Folland Aircraft
Context triple: [Folland Midge, manufacturer, Folland Aircraft]
  • A. Folland Aircraft chosen
    Folland Aircraft was a British aircraft manufacturer best known for producing light fighter and trainer aircraft in the post-World War II era.
  • B. Swearingen Aircraft
    Swearingen Aircraft was an American aircraft manufacturer best known for producing small commuter and business aircraft, including the Metroliner series.
  • C. Ferris Aircraft
    Ferris Aircraft is a fictional aerospace company in DC Comics best known as the workplace of test pilot Hal Jordan, who becomes the superhero Green Lantern.
  • D. Hawker Aircraft
    Hawker Aircraft was a prominent British aircraft manufacturer best known for producing iconic military planes such as the Hawker Hurricane during the early to mid-20th century.
  • E. Piper Aircraft
    Piper Aircraft is an American general aviation manufacturer best known for producing a wide range of popular light aircraft for personal, training, and business use.
  • 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_69e0b4c4cc648190b45fda6e2b20af56 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c1d6bdcc8190ba42c44159a2c0d5 completed April 21, 2026, 12:16 a.m.
Created at: April 16, 2026, 12:27 p.m.