Triple

T14878898
Position Surface form Disambiguated ID Type / Status
Subject Daniel Kwan E349940 entity
Predicate coDirectedWith P17194 FINISHED
Object Daniel Scheinert E375099 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: Daniel Scheinert | Statement: [Daniel Kwan, coDirectedWith, Daniel Scheinert]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daniel Scheinert
Context triple: [Daniel Kwan, coDirectedWith, Daniel Scheinert]
  • A. Daniel Scheinert chosen
    Daniel Scheinert is an American filmmaker, best known as one half of the directing duo Daniels behind the acclaimed film "Everything Everywhere All at Once."
  • B. Daniel Roher
    Daniel Roher is a Canadian documentary filmmaker best known for directing the Oscar-winning political documentary "Navalny."
  • C. Daniel Kurth
    Daniel Kurth is a German local politician who serves as the mayor of the municipality of Panketal in the state of Brandenburg.
  • D. Christopher Franke
    Christopher Franke is a German composer and former Tangerine Dream member best known for his electronic and film scores, including work on science fiction and adventure productions.
  • E. Daniel Scharf
    Daniel Scharf is a film producer best known for his work on the influential 1992 Australian drama "Romper Stomper."
  • 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_69d822ee4f408190b6ac3b2fa434f0df completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded5e622388190b2bf91cd10b9821d completed April 15, 2026, 12:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe8bccc26c8190bf571ea7aee0e0f6 completed May 9, 2026, 1:20 a.m.
Created at: April 10, 2026, 1:55 a.m.