Triple

T11317979
Position Surface form Disambiguated ID Type / Status
Subject To Life E268013 entity
Predicate notablePerformer P17435 FINISHED
Object Leonard Frey E374787 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: Leonard Frey | Statement: [To Life, notablePerformer, Leonard Frey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leonard Frey
Context triple: [To Life, notablePerformer, Leonard Frey]
  • A. Leonard Frey chosen
    Leonard Frey was an American actor best known for his Academy Award–nominated performance as Motel the tailor in the film adaptation of the musical "Fiddler on the Roof."
  • B. Walter Fries
    Walter Fries was a German Wehrmacht general during World War II who commanded armored and infantry units on multiple fronts, including in the Mediterranean theater.
  • C. Charles Leickert
    Charles Leickert was a 19th-century Dutch painter renowned for his atmospheric winter landscapes and cityscapes of the Netherlands.
  • D. Leonard Hirschfield
    Leonard Hirschfield was a cinematographer best known for his work on the 1962 psychological drama film "David and Lisa."
  • E. Henry Freulich
    Henry Freulich was an American cinematographer known for his extensive work on Hollywood films from the 1930s through the 1950s, particularly at Columbia Pictures.
  • 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_69d6aaca5c24819083db46a30d86cb34 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9c3cf748190987838029d9f7fff completed April 9, 2026, 6:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69e6e72931208190b91ef4be770c00d4 completed April 21, 2026, 2:55 a.m.
Created at: April 8, 2026, 9:32 p.m.