Triple

T510970
Position Surface form Disambiguated ID Type / Status
Subject Junkers Ju 87 E10607 entity
Predicate manufacturer P490 FINISHED
Object Junkers E44318 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: Junkers | Statement: [Junkers Ju 87, manufacturer, Junkers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Junkers
Context triple: [Junkers Ju 87, manufacturer, Junkers]
  • A. Junkers chosen
    Junkers was a pioneering German aircraft manufacturer renowned for producing innovative military and civilian airplanes, particularly during the early to mid-20th century.
  • B. Heinkel
    Heinkel was a German aircraft manufacturing company best known for producing military aircraft for Nazi Germany during World War II.
  • C. Dornier Flugzeugwerke
    Dornier Flugzeugwerke was a German aircraft manufacturer best known for producing military aircraft for the Luftwaffe before and during World War II.
  • D. Fieseler
    Fieseler was a German aircraft manufacturer best known for producing innovative World War II aircraft, including the V-1 flying bomb.
  • E. Bayerische Flugzeugwerke
    Bayerische Flugzeugwerke was a German aircraft manufacturer that became known as the predecessor to Messerschmitt AG, producing several notable military aircraft in the interwar and World War II periods.
  • 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_69a2e84a0d08819087e01863fcd9abf1 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f165b91c81908c2d2ba15c64b956 completed Feb. 28, 2026, 1:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4a14e37208190b4df8e75b6fe03fb completed March 1, 2026, 8:27 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.