Triple

T20517954
Position Surface form Disambiguated ID Type / Status
Subject Andrew Koenig E503729 entity
Predicate familyName P18 FINISHED
Object Koenig 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: Koenig | Statement: [Andrew Koenig, familyName, Koenig]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Koenig
Context triple: [Andrew Koenig, familyName, Koenig]
  • A. Kœnig
    Kœnig is a French surname most notably associated with figures such as General Marie-Pierre Kœnig, a prominent military leader during World War II.
  • B. König chosen
    König is a German-language surname borne by numerous individuals, including notable figures in fields such as religion, science, and the arts.
  • C. Kingo
    Kingo is a Japanese given name most notably borne by Tatsuno Kingo, a prominent architect of Japan’s Meiji era.
  • D. Kingo
    Kingo is an Eternal who lives on Earth as a charismatic Bollywood movie star while secretly using his cosmic powers to protect humanity.
  • E. Kenig
    Kenig is a surname most notably associated with Carlos Kenig, an Argentine-American mathematician renowned for his contributions to partial differential equations and harmonic analysis.
  • 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_69e0b4b2aa788190ae9eb37c1d73b1f1 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e69f43e0b08190b043f35645b264a0 completed April 20, 2026, 9:48 p.m.
Created at: April 16, 2026, 11:36 a.m.