Triple

T19000094
Position Surface form Disambiguated ID Type / Status
Subject Dan Feuerriegel E464924 entity
Predicate name P16 FINISHED
Object Dan Feuerriegel 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: Dan Feuerriegel | Statement: [Dan Feuerriegel, name, Dan Feuerriegel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dan Feuerriegel
Context triple: [Dan Feuerriegel, name, Dan Feuerriegel]
  • A. Dan Feuerriegel chosen
    Dan Feuerriegel is an Australian actor best known for his role as the gladiator Agron in the television series Spartacus.
  • B. Daniel von Bargen
    Daniel von Bargen was an American character actor known for his authoritative and often villainous roles in film and television, including appearances in projects like "The General’s Daughter," "Seinfeld," and "Malcolm in the Middle."
  • C. Dan Rieser
    Dan Rieser is an American drummer and percussionist known for his work with various rock, jazz, and Americana artists, including as a member of the country-influenced band The Little Willies.
  • D. Daniel Roher
    Daniel Roher is a Canadian documentary filmmaker best known for directing the Oscar-winning political documentary "Navalny."
  • E. Andrew Doerfer
    Andrew Doerfer is a film editor best known for his work on the movie "Iron Will."
  • 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_69d8dd01a56c81909694a128c66b21d7 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d684d37c8190b975f04a47fa7b92 completed April 20, 2026, 7:32 a.m.
Created at: April 10, 2026, 12:01 p.m.