Triple
T37677481
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shut Up |
E938133
|
entity |
| Predicate | basedOnTelevisionExposureOf |
P200091
|
FINISHED |
| Object | Kelly Osbourne |
—
|
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: Kelly Osbourne | Statement: [Shut Up, basedOnTelevisionExposureOf, Kelly Osbourne]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basedOnTelevisionExposureOf Context triple: [Shut Up, basedOnTelevisionExposureOf, Kelly Osbourne]
-
A.
televisionExposureLevel
Indicates the degree or amount of exposure an entity has to television content.
-
B.
isWatchedOnTelevisionBy
Indicates that an entity (such as a program or event) is being viewed on television by a particular person or audience.
-
C.
mediaExposure
Indicates the extent to which an entity is subjected to or receives attention from media channels such as television, radio, print, or online platforms.
-
D.
providesExposureTo
Indicates that one entity gives another entity the opportunity to be seen, noticed, or become known by a particular audience, environment, or set of influences.
-
E.
televisionNotability
Indicates that an entity is notable or significant specifically for its involvement in television (e.g., TV roles, appearances, or contributions).
- 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_69f76ed7b1408190ba8c93c53cb8becf |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ff70ecc1a481909571b18d56d982b8 |
completed | May 9, 2026, 5:37 p.m. |
| PD | Predicate disambiguation | batch_69ff70322a3c8190837840ea42cd3093 |
completed | May 9, 2026, 5:34 p.m. |
| PDg | Predicate description generation | batch_69ff70ebec7481908d8a4124c8d531df |
completed | May 9, 2026, 5:37 p.m. |
Created at: May 3, 2026, 4:18 p.m.