Triple
T15292488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 1 (Turin Metro) |
E365560
|
entity |
| Predicate | trackGaugeMm |
P391
|
FINISHED |
| Object | 1435 |
—
|
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: 1435 | Statement: [Line 1 (Turin Metro), trackGaugeMm, 1435]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trackGaugeMm Context triple: [Line 1 (Turin Metro), trackGaugeMm, 1435]
-
A.
trackGauge
chosen
Indicates the distance between the inner faces of the rails in a railway track system.
-
B.
trackDiameter
Indicates the diameter measurement of a track, typically specifying the width across its circular or rounded layout.
-
C.
mainTrackDistance
Indicates the distance measured along the primary or main track between two referenced points or entities.
-
D.
trackWidth
Indicates the lateral distance between two parallel tracks or wheels, typically measured from center to center.
-
E.
trackLengthApproxKm
Indicates that one entity has an approximate track length, measured in kilometers, associated with it.
- 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_69d85a103d9081908c1ea6c4c73ac8e3 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03680b60c8190a3ea54a9d34c8105 |
completed | April 16, 2026, 1:08 a.m. |
| PD | Predicate disambiguation | batch_69deca935e2c8190b640987ddfc542b9 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:15 a.m.