Triple
T26589121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Comedy Central Roast of Justin Bieber |
E667296
|
entity |
| Predicate | hasRoastMaster |
P172341
|
FINISHED |
| Object | Kevin Hart |
—
|
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: Kevin Hart | Statement: [The Comedy Central Roast of Justin Bieber, hasRoastMaster, Kevin Hart]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRoastMaster Context triple: [The Comedy Central Roast of Justin Bieber, hasRoastMaster, Kevin Hart]
-
A.
roastProfile
Indicates the specific roasting characteristics or level applied to an item (typically coffee), defining how it was roasted.
-
B.
hasPrimaryBartenderTrait
Indicates that an entity possesses the main or defining characteristic(s) associated with being a bartender.
-
C.
isCookedBy
Indicates that something has been prepared or made ready for eating through cooking by a particular agent.
-
D.
typicalRoastUse
Indicates that something is commonly or characteristically used for roasting.
-
E.
hasMashgiach
Indicates that an entity is supervised or overseen by a mashgiach (a kosher supervisor).
- F. None of above. chosen
Provenance (4 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_69ee9cfb7e548190b60a9031182f5a7e |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f6abe15d5c81909ccf4ce37f78bc43 |
completed | May 3, 2026, 1:58 a.m. |
| PD | Predicate disambiguation | batch_69f6aa1c555081908787dbf76147f180 |
completed | May 3, 2026, 1:51 a.m. |
| PDg | Predicate description generation | batch_69f6aaf31a548190b2f792ff4b8c002a |
completed | May 3, 2026, 1:54 a.m. |
Created at: April 27, 2026, 2:07 a.m.