Triple

T13510926
Position Surface form Disambiguated ID Type / Status
Subject Victor Kilian E321136 entity
Predicate name P16 FINISHED
Object Victor Kilian E321136 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: Victor Kilian | Statement: [Victor Kilian, name, Victor Kilian]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Victor Kilian
Context triple: [Victor Kilian, name, Victor Kilian]
  • A. Victor Kilian chosen
    Victor Kilian was an American character actor known for his prolific work in film and television from the 1920s through the 1970s.
  • B. Charles Geschke
    Charles Geschke was an American computer scientist and entrepreneur best known as the co-founder of Adobe Systems and a pioneer of desktop publishing technologies.
  • C. Mark Kilian
    Mark Kilian is a South African-born film composer known for scoring numerous Hollywood movies and television projects.
  • D. Mark Nielsen
    Mark Nielsen is a film producer best known for his work on Pixar's animated feature "Toy Story 4."
  • E. Andy Hertzfeld
    Andy Hertzfeld is a pioneering software engineer best known as a key member of the original Apple Macintosh development team and a co-creator of the Mac’s graphical user interface.
  • 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_69d807629d6c8190998f1b9bb12d2ed0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaf86a6208190be8c18f7a0158f23 completed April 12, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75490291c8190b5985d8c90ef1af6 completed May 3, 2026, 1:58 p.m.
Created at: April 9, 2026, 9:43 p.m.