Triple

T12278800
Position Surface form Disambiguated ID Type / Status
Subject Taxi E292660 entity
Predicate creator P184 FINISHED
Object Stan Daniels E716735 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: Stan Daniels | Statement: [Taxi, creator, Stan Daniels]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stan Daniels
Context triple: [Taxi, creator, Stan Daniels]
  • A. Stan Daniels chosen
    Stan Daniels was a Canadian-born television writer, producer, and director best known for his work on classic sitcoms such as "The Mary Tyler Moore Show" and "Taxi."
  • B. Bruce Daniels
    Bruce Daniels is a computer scientist and game developer best known for co-founding the pioneering interactive fiction company Infocom.
  • C. Mel Daniels
    Mel Daniels was an American professional basketball center best known as a dominant force in the ABA, where he won multiple MVP awards and championships with the Indiana Pacers.
  • D. Dan Dugmore
    Dan Dugmore is an American session musician and steel guitarist known for his work with prominent country and rock artists.
  • E. Don Taylor
    Don Taylor was an American actor and later film and television director known for roles in classic films such as "Stalag 17" and for directing movies like "Escape from the Planet of the Apes."
  • 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_69d6ab6856488190b5d31178d5015f8e completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91cf1ab8c8190a51f498bfda957d8 completed April 10, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64b8afc2c8190af33f75356376977 completed May 2, 2026, 7:07 p.m.
Created at: April 8, 2026, 9:52 p.m.