Triple
T26852265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanzanian railway network |
E676087
|
entity |
| Predicate | trackGaugeTAZARA |
P391
|
FINISHED |
| Object | 1067 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: 1067 mm | Statement: [Tanzanian railway network, trackGaugeTAZARA, 1067 mm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trackGaugeTAZARA Context triple: [Tanzanian railway network, trackGaugeTAZARA, 1067 mm]
-
A.
trackGauge
chosen
Indicates the distance between the inner faces of the rails in a railway track system.
-
B.
hasMountainRailwayConnectionTo
Indicates that there is a railway line specifically adapted for mountainous terrain that connects one location to another.
-
C.
trailNumber
Indicates that an entity is associated with a specific trail identifier or route number within a trail system.
-
D.
transportSegment
Indicates a distinct portion of a larger journey or route during which something or someone is transported from one point to another.
-
E.
railwayTraffic
Indicates the presence, flow, or management of train movements along railway lines between locations.
- 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_69eee9b9d7708190a15d7485709ae981 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f64dbbaefc8190952b8320bf4397d8 |
completed | May 2, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69f64cacd2c08190aed8a1761d0da679 |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 27, 2026, 5:18 a.m.