Triple
T35471228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nikki Heat book series |
E1025211
|
entity |
| Predicate | televisionFranchise |
P183324
|
FINISHED |
| Object | Castle franchise |
—
|
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: Castle franchise | Statement: [Nikki Heat book series, televisionFranchise, Castle franchise]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: televisionFranchise Context triple: [Nikki Heat book series, televisionFranchise, Castle franchise]
-
A.
televisionUniverse
Indicates that two entities exist within the same fictional television continuity or shared TV universe.
-
B.
notableSeriesFranchise
Indicates that an entity is a significant or well-known installment within a particular series or franchise.
-
C.
fandomFranchise
Indicates that one entity is a fan community or fandom specifically devoted to the other entity as a franchise or media property.
-
D.
televisionShow
Indicates that one entity is a television show associated with, or featured in relation to, another entity.
-
E.
televisionFilm
Indicates that the subject is a television film (a movie produced for or originally distributed via television).
- 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_69f76dfadba0819083456aadcd6864ea |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79da9f80c8190b0afd8509f28747b |
completed | May 3, 2026, 7:10 p.m. |
| PD | Predicate disambiguation | batch_69f79617d40481909ba372f94209c08b |
completed | May 3, 2026, 6:38 p.m. |
| PDg | Predicate description generation | batch_69f79da8d8848190ab5ab1bdad95d58c |
completed | May 3, 2026, 7:10 p.m. |
Created at: May 3, 2026, 4:04 p.m.