Triple
T1825037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aeroexpress train |
E40632
|
entity |
| Predicate | usesExistingRailInfrastructure |
P15040
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Aeroexpress train, usesExistingRailInfrastructure, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesExistingRailInfrastructure Context triple: [Aeroexpress train, usesExistingRailInfrastructure, yes]
-
A.
usesRailInfrastructureOf
chosen
Indicates that one entity operates on, accesses, or otherwise makes use of the rail infrastructure owned or managed by another entity.
-
B.
railwayUse
Indicates that something is used as, or functions in the capacity of, a railway or rail-based transportation facility.
-
C.
hasRailSystem
Indicates that an entity possesses or is served by a rail-based transportation system.
-
D.
railroadMet
Indicates that two or more railroads encountered or connected with each other at a specific place or time.
-
E.
hasRailFacility
Indicates that an entity possesses or is served by a rail-related facility, such as a railway station, terminal, or yard.
- 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_69a8864644bc8190b2358ab897194ac1 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb45402688190b9a535b14030c354 |
completed | March 7, 2026, 5:15 a.m. |
| PD | Predicate disambiguation | batch_69abafd6a9948190ac2b2743db6f8f69 |
completed | March 7, 2026, 4:55 a.m. |
Created at: March 4, 2026, 7:32 p.m.