Triple
T4322631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brooklyn Nine-Nine |
E96553
|
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.
Peter Krause
Peter Krause is an American actor best known for his leading roles in television dramas such as Six Feet Under, Sports Night, and Parenthood.
-
D.
Donald Faison
Donald Faison is an American actor and comedian best known for his role as Dr. Christopher Turk on the television series "Scrubs."
-
E.
Tim Healy
Tim Healy was an Irish nationalist politician, lawyer, and writer who became the first Governor-General of the Irish Free State.
- 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_69b345422aac81909ddbadae437d122e |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b351177eb88190b89fa49a88add5e8 |
completed | March 12, 2026, 11:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5d09165a8819089fbb9b9ed4c82ff |
completed | March 14, 2026, 9:18 p.m. |
Created at: March 12, 2026, 11:12 p.m.