Triple

T19623842
Position Surface form Disambiguated ID Type / Status
Subject Ju 86Z E471082 entity
Predicate manufacturer P490 FINISHED
Object Junkers 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: Junkers | Statement: [Ju 86Z, manufacturer, Junkers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Junkers
Context triple: [Ju 86Z, 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. Junkers
    The Junkers were a powerful class of landowning aristocrats in eastern Germany, especially Prussia, who dominated the military, political, and economic life of the region until the early 20th century.
  • C. Heinkel
    Heinkel was a German aircraft manufacturing company best known for producing military aircraft for Nazi Germany during World War II.
  • D. Dornier Flugzeugwerke
    Dornier Flugzeugwerke was a German aircraft manufacturer best known for producing military aircraft for the Luftwaffe before and during World War II.
  • E. Junkers design bureau
    The Junkers design bureau was a German aircraft engineering office renowned for developing innovative all-metal airplanes for both civilian and military use during the early to mid-20th century.
  • 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_69d8e510fa248190b7afb274a1d4cf73 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e640e8695c81909268c5a91cdbb7fa completed April 20, 2026, 3:06 p.m.
Created at: April 10, 2026, 1:44 p.m.