Triple
T33915309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Car 54, Where Are You? |
E869434
|
entity |
| Predicate | hasSpinOffOrAdaptation |
P7226
|
FINISHED |
| Object | Car 54, Where Are You? (1994 film) |
—
|
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: Car 54, Where Are You? (1994 film) | Statement: [Car 54, Where Are You?, hasSpinOffOrAdaptation, Car 54, Where Are You? (1994 film)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpinOffOrAdaptation Context triple: [Car 54, Where Are You?, hasSpinOffOrAdaptation, Car 54, Where Are You? (1994 film)]
-
A.
hasSpinOff
chosen
Indicates that one entity is a derivative or spin-off product, work, or organization that originated from another entity.
-
B.
hasFranchiseOrSpinOff
Indicates that one work, series, or product is related to another as a franchise entry or a spin-off derived from it.
-
C.
hasSpinOffLabel
Indicates that one entity serves as a spin-off label or subsidiary label that originated from another label entity.
-
D.
hasSpinOffDevelopment
Indicates that one entity has led to or produced a derivative or spin-off development based on it.
-
E.
hasSpinOffPlatform
Indicates that one entity has given rise to or is associated with a derivative or spin-off platform based on the original.
- 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_69f3499869bc8190b6c33a81686af226 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fe031bc6208190860099aef72d8dcb |
completed | May 8, 2026, 3:36 p.m. |
| PD | Predicate disambiguation | batch_69fe014c8b388190b5d4e0cb95ee2be5 |
completed | May 8, 2026, 3:29 p.m. |
Created at: May 1, 2026, 1:48 a.m.