Triple

T16529946
Position Surface form Disambiguated ID Type / Status
Subject Thrust2 E401536 entity
Predicate sponsor P67 FINISHED
Object GKN E812842 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: GKN | Statement: [Thrust2, sponsor, GKN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GKN
Context triple: [Thrust2, sponsor, GKN]
  • A. GKN Sankey
    GKN Sankey was a British engineering and manufacturing company best known for producing military vehicles and automotive components.
  • B. GKN Aerospace chosen
    GKN Aerospace is a global aerospace engineering company that designs and manufactures advanced aircraft structures, engine components, and systems for commercial, military, and space applications.
  • C. Bendix
    Bendix is a surname most notably associated with American actor William Bendix, known for his roles in mid-20th-century film and radio.
  • D. Korgen
    Korgen is a village in Nordland county, Norway, known as the main local hub for services and administration in the municipality of Hemnes.
  • E. Bristol Automotive
    Bristol Automotive is a British film production company known for its involvement in the making of the historical drama "The Imitation Game."
  • 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_69d883838abc8190bc79cb2d41733ce2 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32ed625208190a68b879266b05b3f completed April 18, 2026, 7:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00609129808190b893346e06deb944 completed May 10, 2026, 10:40 a.m.
Created at: April 10, 2026, 5:14 a.m.