Triple

T19521418
Position Surface form Disambiguated ID Type / Status
Subject The Perfect Score E488408 entity
Predicate starredActor P5563 FINISHED
Object Bryan Greenberg NE NERFINISHED

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: Bryan Greenberg | Statement: [The Perfect Score, starredActor, Bryan Greenberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bryan Greenberg
Context triple: [The Perfect Score, starredActor, Bryan Greenberg]
  • A. Bryan Greenberg chosen
    Bryan Greenberg is an American actor and singer best known for his roles in television series like "One Tree Hill" and "How to Make It in America," as well as various romantic comedies.
  • B. Matt Greenberg
    Matt Greenberg is a screenwriter and film producer known for his work on various horror and thriller projects in American cinema.
  • C. Kenny Greenberg
    Kenny Greenberg is an American guitarist and record producer known for his extensive work in country and rock music with numerous high-profile artists.
  • D. Josh Weinstock
    Josh Weinstock is a film and television producer known for his work on projects such as the drama "Nightingale."
  • E. Steve Greenberg
    Steve Greenberg is an American sports media executive and entrepreneur best known for founding the Classic Sports Network, which later became ESPN Classic.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8da8bec819081f400199491ccc3 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e635a0b37c8190b70b7427c2e85f59 completed April 20, 2026, 2:18 p.m.
Created at: April 10, 2026, 1:40 p.m.