Triple
T33420324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McQ |
E855828
|
entity |
| Predicate | hasVehicleSetPiece |
P37148
|
FINISHED |
| Object | car chases on the beach |
—
|
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: car chases on the beach | Statement: [McQ, hasVehicleSetPiece, car chases on the beach]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVehicleSetPiece Context triple: [McQ, hasVehicleSetPiece, car chases on the beach]
-
A.
hasSetPiece
chosen
Indicates that an event, scene, or work includes a distinct, often elaborate set piece as a notable component.
-
B.
hasVehicle
Indicates that one entity possesses, owns, or is assigned a vehicle.
-
C.
hasVehicleCollection
Indicates that an entity possesses or maintains a set or collection of vehicles.
-
D.
hasVehicleDeck
Indicates that something (typically a vessel or structure) includes a dedicated deck or level designed for carrying or transporting vehicles.
-
E.
hasFictionalVehicle
Indicates that one entity possesses, controls, or is associated with a vehicle that exists only in a fictional or imaginary context.
- 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_69f3496fdf0081908c1aa30870ce518b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f71362f1448190985a80ce7af475cb |
completed | May 3, 2026, 9:20 a.m. |
| PD | Predicate disambiguation | batch_69f7127884388190884f23d181a65d19 |
completed | May 3, 2026, 9:16 a.m. |
Created at: May 1, 2026, 1:36 a.m.