Triple
T38550504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brian Earl Spilner |
E925096
|
entity |
| Predicate | coverStoryVehicle |
P61976
|
FINISHED |
| Object | Mitsubishi Eclipse |
—
|
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: Mitsubishi Eclipse | Statement: [Brian Earl Spilner, coverStoryVehicle, Mitsubishi Eclipse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coverStoryVehicle Context triple: [Brian Earl Spilner, coverStoryVehicle, Mitsubishi Eclipse]
-
A.
vehicleBase
Indicates that one entity serves as the foundational or underlying base for a vehicle-related entity or system.
-
B.
depictsVehicle
Indicates that one entity visually represents or portrays a vehicle in an image, artwork, or other depiction.
-
C.
mainVehicle
chosen
Indicates that one vehicle is the primary or most important vehicle associated with a given entity or context.
-
D.
producedVehicle
Indicates that one entity manufactured or created a particular vehicle.
-
E.
vehicleUsed
Indicates that a particular vehicle is utilized or employed in performing an action, event, or activity.
- 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_69f76eaeb69c8190b367df9330d6f6af |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fd82ed2a4c81908bd7797fbd2e3d08 |
completed | May 8, 2026, 6:30 a.m. |
| PD | Predicate disambiguation | batch_69fd814cc10481908e4f8123d35a5d0c |
completed | May 8, 2026, 6:23 a.m. |
Created at: May 3, 2026, 4:32 p.m.