Triple
T37874657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crash 3 |
E944686
|
entity |
| Predicate | hasVehicleLevel |
P139437
|
FINISHED |
| Object | motorcycle levels |
—
|
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: motorcycle levels | Statement: [Crash 3, hasVehicleLevel, motorcycle levels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVehicleLevel Context triple: [Crash 3, hasVehicleLevel, motorcycle levels]
-
A.
includesVehicleLevel
chosen
Indicates that something encompasses or applies to a specific level or category associated with a vehicle.
-
B.
hasVehicularActivityLevel
Indicates the degree or intensity of vehicular activity associated with an entity, such as traffic volume or frequency of vehicle use.
-
C.
hasVehicle
Indicates that one entity possesses, owns, or is assigned a vehicle.
-
D.
hasVehicleFeature
Indicates that a vehicle possesses, includes, or is equipped with a specific feature or characteristic.
-
E.
SAELevel
Indicates the level or degree of a subject according to the SAE (e.g., standard, classification, or grading) scale.
- 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_69f76eef55d481908ca6660b4b532550 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd166a488190b1bf9316b0790801 |
completed | May 6, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:19 p.m.