Triple

T8207635
Position Surface form Disambiguated ID Type / Status
Subject The Night Club Lady E191726 entity
Predicate cinematographyBy P1953 FINISHED
Object Ted Tetzlaff E404535 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: Ted Tetzlaff | Statement: [The Night Club Lady, cinematographyBy, Ted Tetzlaff]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ted Tetzlaff
Context triple: [The Night Club Lady, cinematographyBy, Ted Tetzlaff]
  • A. Ted Tetzlaff chosen
    Ted Tetzlaff was an American cinematographer and film director best known for his stylish black-and-white photography on classic Hollywood films of the 1930s and 1940s.
  • B. Eric Lamonsoff
    Eric Lamonsoff is a bumbling yet big-hearted family man and close friend of Lenny Feder in the Grown Ups comedy film series.
  • C. Eric Wetzels
    Eric Wetzels is a Dutch politician who serves as the chairperson of the People's Party for Freedom and Democracy (VVD).
  • D. Ed Schafer
    Ed Schafer is an American politician and businessman who served as Governor of North Dakota and later as the United States Secretary of Agriculture under President George W. Bush.
  • E. Kevin Biegel
    Kevin Biegel is an American television writer and producer best known for co-creating the sitcom Cougar Town and working on shows like Scrubs and Enlisted.
  • 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_69ca82c7f3e08190857bf1fc63b2a10c completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb726d26ec8190957da68227f5ce61 completed March 31, 2026, 7:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69cdc69b9b8c819082a164433312166e completed April 2, 2026, 1:30 a.m.
Created at: March 30, 2026, 5:43 p.m.