Triple
T33835937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SESM ESM 500 |
E867233
|
entity |
| Predicate | designedForVehicleClass |
P97747
|
FINISHED |
| Object | heavy tracked vehicles |
—
|
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: heavy tracked vehicles | Statement: [SESM ESM 500, designedForVehicleClass, heavy tracked vehicles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: designedForVehicleClass Context triple: [SESM ESM 500, designedForVehicleClass, heavy tracked vehicles]
-
A.
intendedVehicleClass
chosen
Indicates that one entity is designed or specified to be used with, or is appropriate for, a particular class or category of vehicle.
-
B.
intendedForVehicle
Indicates that something is designed, meant, or suitable to be used with or by a particular vehicle.
-
C.
intendedVehicle
Indicates that one entity is the vehicle that another entity plans or is meant to use.
-
D.
appliedToVehicleType
Indicates that something (such as a rule, restriction, or condition) is specifically applicable to a particular type or category of vehicle.
-
E.
basedOnVehicle
Indicates that one entity is derived from, modeled after, or otherwise conceptually or functionally based on a particular vehicle.
- 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_69f34992ad40819087760ed939bd2a7a |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69febce5877c8190a5e000ef5331ec88 |
completed | May 9, 2026, 4:49 a.m. |
| PD | Predicate disambiguation | batch_69febad1cd588190abc7686bcb39a371 |
completed | May 9, 2026, 4:40 a.m. |
Created at: May 1, 2026, 1:47 a.m.