Triple
T34097429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marriage Boot Camp: Reality Stars |
E874468
|
entity |
| Predicate | isTelevisionFranchiseEntry |
P7740
|
FINISHED |
| Object | Marriage Boot Camp |
—
|
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: Marriage Boot Camp | Statement: [Marriage Boot Camp: Reality Stars, isTelevisionFranchiseEntry, Marriage Boot Camp]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isTelevisionFranchiseEntry Context triple: [Marriage Boot Camp: Reality Stars, isTelevisionFranchiseEntry, Marriage Boot Camp]
-
A.
fandomFranchise
Indicates that one entity is a fan community or fandom specifically devoted to the other entity as a franchise or media property.
-
B.
notableSeriesFranchise
Indicates that an entity is a significant or well-known installment within a particular series or franchise.
-
C.
hasMediaFranchise
chosen
Indicates that one entity is part of, or belongs to, a larger media franchise represented by another entity.
-
D.
basedOnShowFranchise
Indicates that one entity is derived from, adapted from, or otherwise created based on the concept, content, or brand of a particular show franchise.
-
E.
isTelevisionAdaptationOf
Indicates that a television show is an adaptation derived from the story, characters, or content of another original work.
- 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_69f349a735208190a1dbfb1c2a121059 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f70c6153e48190879589fa9eab790f |
completed | May 3, 2026, 8:50 a.m. |
| PD | Predicate disambiguation | batch_69f70ac0170c819098e3b8e41d02efef |
completed | May 3, 2026, 8:43 a.m. |
Created at: May 1, 2026, 1:53 a.m.