Triple
T37353578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Younan Nowzaradan |
E927391
|
entity |
| Predicate | genreOfTelevision |
P83375
|
FINISHED |
| Object | reality television |
—
|
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: reality television | Statement: [Younan Nowzaradan, genreOfTelevision, reality television]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreOfTelevision Context triple: [Younan Nowzaradan, genreOfTelevision, reality television]
-
A.
tvGenre
chosen
Indicates the genre or category to which a television show or program belongs.
-
B.
televisionShow
Indicates that one entity is a television show associated with, or featured in relation to, another entity.
-
C.
televisionCategory
Indicates the classification or genre category assigned to a television-related entity (such as a show, channel, or program).
-
D.
visualGenre
Indicates the visual or stylistic category to which something belongs, such as its artistic or cinematic genre.
-
E.
entertainmentType
Indicates the kind or category of entertainment associated with an entity or event.
- F. None of above.
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_69f76eb5e034819088e53ab5b7909a68 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb9e1845e881908d19158440cf3b87 |
completed | May 6, 2026, 8:01 p.m. |
| PD | Predicate disambiguation | batch_69fb8d08d6988190a00794ac26078348 |
completed | May 6, 2026, 6:48 p.m. |
Created at: May 3, 2026, 4:16 p.m.