Triple
T21052387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Línea 1 del Metro de Lima y Callao concessionaire |
E518620
|
entity |
| Predicate | operatesOnRailGauge |
P5070
|
FINISHED |
| Object | standard gauge |
—
|
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: standard gauge | Statement: [Línea 1 del Metro de Lima y Callao concessionaire, operatesOnRailGauge, standard gauge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatesOnRailGauge Context triple: [Línea 1 del Metro de Lima y Callao concessionaire, operatesOnRailGauge, standard gauge]
-
A.
usesRailGauge
chosen
Indicates that one entity (typically a railway system or line) operates using the specified rail gauge measurement of the other entity.
-
B.
railwayGaugeContext
Indicates the specific track gauge standard or measurement that applies to, or is used in, a given railway-related context.
-
C.
hasRailWidth
Indicates that one entity has a specified width measurement for its rail or rails.
-
D.
railStandard
Indicates that something conforms to, uses, or is governed by a particular railway or rail transport standard.
-
E.
hasRail
Indicates that something is equipped with, includes, or is connected to a rail or rail system.
- 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_69e0b5053ac48190921529544959e906 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fd7cabe881909e6b258a14d501a6 |
completed | April 21, 2026, 4:30 a.m. |
| PD | Predicate disambiguation | batch_69e5dbf6728881908a2a43a5c8804a2a |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 16, 2026, 2:35 p.m.