Triple
T34930296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matadi–Kinshasa corridor |
E1007412
|
entity |
| Predicate | gaugeOfRailComponent |
P47503
|
FINISHED |
| Object | 1,067 mm |
—
|
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: 1,067 mm | Statement: [Matadi–Kinshasa corridor, gaugeOfRailComponent, 1,067 mm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gaugeOfRailComponent Context triple: [Matadi–Kinshasa corridor, gaugeOfRailComponent, 1,067 mm]
-
A.
usesRailGauge
Indicates that one entity (typically a railway system or line) operates using the specified rail gauge measurement of the other entity.
-
B.
railwayGaugeContext
chosen
Indicates the specific track gauge standard or measurement that applies to, or is used in, a given railway-related context.
-
C.
gaugeCompatibleWith
Indicates that one gauge can be properly used with, mounted to, or function correctly in conjunction with another specified component or system.
-
D.
gaugeType
Indicates the specific kind or category of gauge associated with an entity or measurement.
-
E.
gaugeGroup
Indicates a relationship where a physical or theoretical model is associated with the gauge group that defines its underlying symmetry structure.
- 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_69f76dc3d83881909d5c3c14455cfa2c |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f782c98fa08190870b68de2c1ff26a |
completed | May 3, 2026, 5:15 p.m. |
| PD | Predicate disambiguation | batch_69f781020cc4819088c40cb8589504e4 |
completed | May 3, 2026, 5:08 p.m. |
Created at: May 3, 2026, 4 p.m.