Triple
T29048328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MP series (Matériel Pneumatique) |
E735195
|
entity |
| Predicate | runningGearType |
P85303
|
FINISHED |
| Object | rubber-tyred |
—
|
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: rubber-tyred | Statement: [MP series (Matériel Pneumatique), runningGearType, rubber-tyred]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runningGearType Context triple: [MP series (Matériel Pneumatique), runningGearType, rubber-tyred]
-
A.
hasRunningGear
chosen
Indicates that an entity is equipped with or possesses running gear, such as the mechanical components that enable movement or operation.
-
B.
typicalGear
Indicates that the object represents the usual or standard equipment or gear commonly associated with the subject.
-
C.
goesOnTheRunWith
Indicates that one entity flees or escapes together with another entity, sharing the act of going on the run.
-
D.
runningStyle
Indicates the characteristic manner or form in which an entity performs running.
-
E.
runningTerrain
Indicates the type of ground or surface on which the running activity takes place.
- 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_69f077e64b88819094d37bdbca8191b3 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f66063cc04819098c27a663055d3d8 |
completed | May 2, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69f659d297cc8190b2b962ba30a1edb3 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 10:06 a.m.