Triple

T13469678
Position Surface form Disambiguated ID Type / Status
Subject Kalle E311594 entity
Predicate hasVariant P455 FINISHED
Object Karl unclear NED1 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: Karl | Statement: [Kalle, hasVariant, Karl]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Karl
Context triple: [Kalle, hasVariant, Karl]
  • A. Karl
    Karl is the given first name of Charles Proteus Steinmetz, the renowned German-American mathematician and electrical engineer who revolutionized the understanding of alternating current systems.
  • B. Karl
    Karl is a ruthless, long-haired German terrorist and Hans Gruber’s vengeful right-hand man in the action film "Die Hard."
  • C. Karl
    Karl is the given name of Karl Ritter von Halt, a notable German sports official and International Olympic Committee member in the early to mid-20th century.
  • D. Karl
    Karl Lepsius was a pioneering 19th-century German Egyptologist and linguist known for his foundational work in recording and deciphering ancient Egyptian monuments and texts.
  • E. Karl
    Karl is the given name of Karl Liebknecht, the German socialist politician and co-founder of the Communist Party of Germany.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

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_69d806a938b8819097ec43a2229fc7f9 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaf21e46081908a00c9acf54f270f completed April 12, 2026, 2:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7942424bc8190af98462f6b7a93a4 completed May 3, 2026, 6:29 p.m.
Created at: April 9, 2026, 9:42 p.m.