Triple
T27531532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christine |
E694983
|
entity |
| Predicate | featuresVehicleModel |
P16722
|
FINISHED |
| Object | 1958 Plymouth Fury |
—
|
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: 1958 Plymouth Fury | Statement: [Christine, featuresVehicleModel, 1958 Plymouth Fury]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresVehicleModel Context triple: [Christine, featuresVehicleModel, 1958 Plymouth Fury]
-
A.
featuresVehicle
chosen
Indicates that one entity includes, presents, or prominently incorporates a particular vehicle as part of its content, composition, or offering.
-
B.
carModel
Indicates the specific model designation of a car within a particular make or brand.
-
C.
vehicleVariant
Indicates that one vehicle is a specific version, model, or configuration variant of another related vehicle.
-
D.
vehicleName
Indicates the specific name or designation assigned to a vehicle.
-
E.
vehicleBase
Indicates that one entity serves as the foundational or underlying base for a vehicle-related entity or system.
- 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_69ef538608b081908b9f659bb09d5e0f |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69fd57ba740c8190bd1d40166fccccb7 |
completed | May 8, 2026, 3:25 a.m. |
| PD | Predicate disambiguation | batch_69fd55ee82b881908a639da3a41b3af6 |
completed | May 8, 2026, 3:18 a.m. |
Created at: April 27, 2026, 1:26 p.m.