Triple
T15427057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turin–Cuneo railway |
E369537
|
entity |
| Predicate | hasRailwaySystem |
P522
|
FINISHED |
| Object | Italian standard gauge network |
—
|
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: Italian standard gauge network | Statement: [Turin–Cuneo railway, hasRailwaySystem, Italian standard gauge network]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRailwaySystem Context triple: [Turin–Cuneo railway, hasRailwaySystem, Italian standard gauge network]
-
A.
hasRailSystem
chosen
Indicates that an entity possesses or is served by a rail-based transportation system.
-
B.
hasRailwayInfrastructureType
Indicates that an entity possesses or is associated with a specific type or category of railway infrastructure.
-
C.
usesRailInfrastructureOf
Indicates that one entity operates on, accesses, or otherwise makes use of the rail infrastructure owned or managed by another entity.
-
D.
railSystemType
Indicates the specific category or classification of a rail transportation system that an entity belongs to or operates within.
-
E.
hasPassengerRailConnection
Indicates that there exists a passenger rail service linking one location or transport node to another.
- 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_69d85a1849f48190bf898068b2806fae |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03ec1fb288190a3625b8e4f487dd1 |
completed | April 16, 2026, 1:43 a.m. |
| PD | Predicate disambiguation | batch_69ded27f45548190a6d2b1b85cb47444 |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:20 a.m.