Triple

T21900180
Position Surface form Disambiguated ID Type / Status
Subject Jack Crusher E540786 entity
Predicate createdBy P806 FINISHED
Object Kirsten Beyer 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: Kirsten Beyer | Statement: [Jack Crusher, createdBy, Kirsten Beyer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kirsten Beyer
Context triple: [Jack Crusher, createdBy, Kirsten Beyer]
  • A. Kirsten Beyer chosen
    Kirsten Beyer is an American author and television writer best known for her work on Star Trek novels and for helping develop and write modern Star Trek series such as Star Trek: Discovery and Star Trek: Picard.
  • B. Kirstin Bauch
    Kirstin Bauch is a German politician who serves as the borough mayor of Charlottenburg-Wilmersdorf in Berlin.
  • C. Kirsten Liegmann
    Kirsten Liegmann is known as the wife of prominent American antiwar activist and Chicago Seven defendant Rennie Davis.
  • D. Kirsten Mehr
    Kirsten Mehr is the German-born wife of British politician and former UKIP leader Nigel Farage.
  • E. Kirsten Vangsness
    Kirsten Vangsness is an American actress best known for her role as technical analyst Penelope Garcia on the television series "Criminal Minds."
  • 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_69e0c47b4e8c81908c8076eaa4c8e4f2 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f11fca2bf88190b2a5b912aa102513 completed April 28, 2026, 8:59 p.m.
Created at: April 16, 2026, 7:07 p.m.