Triple
T31319197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tasqueña Metro station complex |
E798678
|
entity |
| Predicate | railGaugeOfConnectedLightRail |
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: [Tasqueña Metro station complex, railGaugeOfConnectedLightRail, standard gauge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railGaugeOfConnectedLightRail Context triple: [Tasqueña Metro station complex, railGaugeOfConnectedLightRail, standard gauge]
-
A.
lightRailNetwork
Indicates a relationship where an area, city, or region is served by or contains a light rail transit network.
-
B.
usesRailGauge
chosen
Indicates that one entity (typically a railway system or line) operates using the specified rail gauge measurement of the other entity.
-
C.
hasLightRailSystem
Indicates that a place possesses and operates a light rail transit system.
-
D.
railwayGaugeContext
Indicates the specific track gauge standard or measurement that applies to, or is used in, a given railway-related context.
-
E.
lightRailSystemName
Indicates the name assigned to a particular light rail transit 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_69f224e1932c81908fef14f7b03a10b7 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69eab7980819083ab0ee519699561 |
completed | May 3, 2026, 1:02 a.m. |
| PD | Predicate disambiguation | batch_69f69d1d25e88190a7f57d323574da90 |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 29, 2026, 9:15 p.m.