Triple

T3018083
Position Surface form Disambiguated ID Type / Status
Subject As Young as You Feel E82385 entity
Predicate starring P1507 FINISHED
Object Albert Dekker E27967 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: Albert Dekker | Statement: [As Young as You Feel, starring, Albert Dekker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Albert Dekker
Context triple: [As Young as You Feel, starring, Albert Dekker]
  • A. Albert Dekker chosen
    Albert Dekker was an American character actor known for his prolific film, stage, and television career from the 1930s to the 1960s, often playing complex or villainous roles.
  • B. Marvin DeWinter
    Marvin DeWinter was an architect known for designing the Gerald R. Ford Presidential Museum in Grand Rapids, Michigan.
  • C. Max Deuring
    Max Deuring was a German mathematician known for his influential work in algebraic number theory and the theory of algebraic function fields.
  • D. Gustav Kleikamp
    Gustav Kleikamp was a German naval officer and rear admiral in the Kriegsmarine during World War II, known for commanding forces in the opening attack on Poland.
  • E. Fred J. Koenekamp
    Fred J. Koenekamp was an American cinematographer renowned for his work on major films of the 1970s and 1980s, earning an Academy Award and multiple nominations for his visually striking photography.
  • 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_69ad8b1eb53481908c39bbcd1ec104b2 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9a90ea64819080620e60bbd6aa24 completed March 8, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1eee74390819087e48b67ed4a9f27 completed March 11, 2026, 10:38 p.m.
Created at: March 8, 2026, 3 p.m.