Triple

T11093992
Position Surface form Disambiguated ID Type / Status
Subject The Good Nurse E262326 entity
Predicate producer P490 FINISHED
Object Scott Franklin E180092 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: Scott Franklin | Statement: [The Good Nurse, producer, Scott Franklin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Scott Franklin
Context triple: [The Good Nurse, producer, Scott Franklin]
  • A. Scott Franklin chosen
    Scott Franklin is an American film producer known for his frequent collaborations with director Darren Aronofsky on acclaimed movies such as Black Swan and The Wrestler.
  • B. Dean Franklin
    Dean Franklin is a screenwriter best known for his work on the classic World War I film "The Fighting 69th."
  • C. Don Franklin
    Don Franklin is an American actor best known for his roles in science fiction and adventure television series, including a prominent part on SeaQuest DSV.
  • D. Richard Franklin
    Richard Franklin was a British actor best known for playing Captain Mike Yates in the classic science fiction television series Doctor Who.
  • E. Vaughn Franklin
    Vaughn Franklin is one of the children of renowned Baptist minister and civil rights activist C. L. Franklin.
  • 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_69d6aa9a40d88190a373e2c7e48285db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d799ed12d88190a4ad8c346d68f11f completed April 9, 2026, 12:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69e42d69c8b4819092614e83e855430e completed April 19, 2026, 1:18 a.m.
Created at: April 8, 2026, 9:27 p.m.