Triple
T33986779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Long Island Causeway tollbooth |
E871431
|
entity |
| Predicate | vehicleInScene |
P178671
|
FINISHED |
| Object | Sonny Corleone's car |
—
|
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: Sonny Corleone's car | Statement: [Long Island Causeway tollbooth, vehicleInScene, Sonny Corleone's car]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vehicleInScene Context triple: [Long Island Causeway tollbooth, vehicleInScene, Sonny Corleone's car]
-
A.
vehicleBase
Indicates that one entity serves as the foundational or underlying base for a vehicle-related entity or system.
-
B.
vehicleFor
Indicates that one entity serves as the means of transportation or conveyance for another entity.
-
C.
depictsVehicle
Indicates that one entity visually represents or portrays a vehicle in an image, artwork, or other depiction.
-
D.
controlVehicle
Indicates having the authority or ability to direct, operate, or manage the movement and functioning of a vehicle.
-
E.
vehicleToLoad
Indicates a relationship where a vehicle is associated with, assigned to, or responsible for transporting a particular load.
- 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_69f3499e964c8190b674b03f6f791b4b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f713bfdc148190a249a7874320bab8 |
completed | May 3, 2026, 9:22 a.m. |
| PD | Predicate disambiguation | batch_69f7127884388190884f23d181a65d19 |
completed | May 3, 2026, 9:16 a.m. |
| PDg | Predicate description generation | batch_69f7135fa2988190a20a94cfe616d754 |
completed | May 3, 2026, 9:20 a.m. |
Created at: May 1, 2026, 1:50 a.m.