Triple

T1129693
Position Surface form Disambiguated ID Type / Status
Subject Brooklyn Nine-Nine E22999 entity
Predicate starredActor P5563 FINISHED
Object Andre Braugher E145629 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: Andre Braugher | Statement: [Brooklyn Nine-Nine, starredActor, Andre Braugher]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Andre Braugher
Context triple: [Brooklyn Nine-Nine, starredActor, Andre Braugher]
  • A. Andre Braugher chosen
    Andre Braugher is an American actor acclaimed for his powerful dramatic roles and his Emmy-winning performances in both television and film.
  • B. Thomas Haden Church
    Thomas Haden Church is an American actor known for roles in the TV series "Wings" and films such as "Sideways" and "Spider-Man 3."
  • C. Donald Faison
    Donald Faison is an American actor and comedian best known for his role as Dr. Christopher Turk on the television series "Scrubs."
  • D. Dennis Franz
    Dennis Franz is an American actor best known for his acclaimed portrayal of Detective Andy Sipowicz on the television series "NYPD Blue."
  • E. Joel Murray
    Joel Murray is an American actor and comedian known for his character roles in film and television, as well as for his voice work in animated projects.
  • 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_69a493ec75988190b63a11bafaec29b4 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4bbf979108190adad7073c8275dd2 completed March 1, 2026, 10:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69aca2e36fc081908de3b67293c7bbf6 completed March 7, 2026, 10:12 p.m.
Created at: March 1, 2026, 7:44 p.m.