Triple
T20079851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UTDC CLRV |
E499967
|
entity |
| Predicate | bogieConfiguration |
P44072
|
FINISHED |
| Object | two trucks |
—
|
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: two trucks | Statement: [UTDC CLRV, bogieConfiguration, two trucks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bogieConfiguration Context triple: [UTDC CLRV, bogieConfiguration, two trucks]
-
A.
bogieType
chosen
Indicates the specific configuration or classification of a vehicle’s bogie (wheel assembly) used in its design or operation.
-
B.
hasBogieCount
Indicates the number of bogies (wheel assemblies) associated with or assigned to an entity.
-
C.
locomotiveConfiguration
Indicates the specific arrangement and type of power and running units (e.g., wheel or axle layout) that define how a locomotive is configured.
-
D.
hasAxleConfiguration
Indicates that an entity is associated with a specific arrangement or configuration of its axles.
-
E.
frontAxleConfiguration
Indicates the specific structural or mechanical arrangement of the vehicle’s front axle.
- 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_69da627770948190997f486f9a2e370f |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6643f93208190ae2a413f88ea9aed |
completed | April 20, 2026, 5:37 p.m. |
| PD | Predicate disambiguation | batch_69e54cf369b88190931532420517dac7 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:40 p.m.