Triple
T26589120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Comedy Central Roast of Justin Bieber |
E667296
|
entity |
| Predicate | featuresRoastee |
P188866
|
FINISHED |
| Object | Justin Bieber |
—
|
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: Justin Bieber | Statement: [The Comedy Central Roast of Justin Bieber, featuresRoastee, Justin Bieber]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresRoastee Context triple: [The Comedy Central Roast of Justin Bieber, featuresRoastee, Justin Bieber]
-
A.
hasRoastType
Indicates that one entity is characterized by or associated with a specific roast type of another entity.
-
B.
roastProfile
Indicates the specific roasting characteristics or level applied to an item (typically coffee), defining how it was roasted.
-
C.
featuresBeverage
Indicates that one entity includes, offers, or presents a particular beverage as part of its contents, services, or characteristics.
-
D.
coffeeProfile
Indicates the characteristic flavor, aroma, and strength attributes that define a particular coffee.
-
E.
coffeeVariety
Indicates a relationship where a specific type or variety of coffee is associated with a coffee-related entity (such as a product, beverage, or plant).
- 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_69fbaf18085481908c774e8f8bbb9a41 |
completed | May 6, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69fbadf1e6008190a71bbd196ba06844 |
completed | May 6, 2026, 9:09 p.m. |
| PDg | Predicate description generation | batch_69fbaebbb7f88190b4edfd9b83550aad |
completed | May 6, 2026, 9:12 p.m. |
Created at: April 27, 2026, 2:07 a.m.