Triple
T4593894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | European Rally Championship |
E103561
|
entity |
| Predicate | usesVehicleClass |
P1776
|
FINISHED |
| Object | Rally2 cars |
—
|
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: Rally2 cars | Statement: [European Rally Championship, usesVehicleClass, Rally2 cars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesVehicleClass Context triple: [European Rally Championship, usesVehicleClass, Rally2 cars]
-
A.
vehicleUsed
Indicates that a particular vehicle is utilized or employed in performing an action, event, or activity.
-
B.
vehicleType
chosen
Indicates the specific kind or category of vehicle associated with an entity (e.g., car, bus, bicycle).
-
C.
associatedVehicleWeightClass
Indicates the weight classification category that is linked or assigned to a particular vehicle.
-
D.
appliedToVehicleType
Indicates that something (such as a rule, restriction, or condition) is specifically applicable to a particular type or category of vehicle.
-
E.
intendedVehicle
Indicates that one entity is the vehicle that another entity plans or is meant to use.
- 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_69bd43dccaf08190aa89e9991a289719 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd593e115081909b11149e02fe4ef3 |
completed | March 20, 2026, 2:27 p.m. |
| PD | Predicate disambiguation | batch_69bd522c811c81909aae4feadae33174 |
completed | March 20, 2026, 1:57 p.m. |
Created at: March 20, 2026, 1:11 p.m.