Triple
T26589136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Comedy Central Roast of Justin Bieber |
E667296
|
entity |
| Predicate | hasRoastType |
P172775
|
FINISHED |
| Object | celebrity roast |
—
|
LITERAL 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: celebrity roast | Statement: [The Comedy Central Roast of Justin Bieber, hasRoastType, celebrity roast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRoastType Context triple: [The Comedy Central Roast of Justin Bieber, hasRoastType, celebrity roast]
-
A.
hasRoastMaster
Indicates that something is associated with or assigned a specific roast master responsible for overseeing its roasting process.
-
B.
typicalRoastUse
Indicates that something is commonly or characteristically used for roasting.
-
C.
roastProfile
Indicates the specific roasting characteristics or level applied to an item (typically coffee), defining how it was roasted.
-
D.
hasCaffeinatedOption
Indicates that something offers or includes at least one option that contains caffeine.
-
E.
hasTeeType
Indicates that an entity (typically a golf hole or course) is associated with a specific type or category of tee.
- 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_69f6b0d21dd08190a9883ff71c94c71c |
completed | May 3, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69f6aca204148190850a3dc325bc07b7 |
completed | May 3, 2026, 2:02 a.m. |
| PDg | Predicate description generation | batch_69f6afeaaef88190aefa97e83f8db906 |
completed | May 3, 2026, 2:16 a.m. |
Created at: April 27, 2026, 2:07 a.m.