Triple
T8826950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris–Clermont-Ferrand |
E210037
|
entity |
| Predicate | usesConventionalRailInfrastructure |
P63327
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Paris–Clermont-Ferrand, usesConventionalRailInfrastructure, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesConventionalRailInfrastructure Context triple: [Paris–Clermont-Ferrand, usesConventionalRailInfrastructure, true]
-
A.
usesRailInfrastructureOf
Indicates that one entity operates on, accesses, or otherwise makes use of the rail infrastructure owned or managed by another entity.
-
B.
hasRailwayInfrastructureType
chosen
Indicates that an entity possesses or is associated with a specific type or category of railway infrastructure.
-
C.
hasRailSystem
Indicates that an entity possesses or is served by a rail-based transportation system.
-
D.
railwayUse
Indicates that something is used as, or functions in the capacity of, a railway or rail-based transportation facility.
-
E.
isElectricRailway
Indicates that a given railway system operates using electric power rather than diesel or other forms of propulsion.
- 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_69ca8365b28081909e48e45e95dfc405 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc6034e8dc819099116d772e87569a |
completed | April 1, 2026, midnight |
| PD | Predicate disambiguation | batch_69cc5c23d08481908d8c9b0ad3d1dc00 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:46 p.m.