Triple
T21800069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glasgow Cross |
E538213
|
entity |
| Predicate | proximityToRail |
P25143
|
FINISHED |
| Object | near Argyle Street railway station |
—
|
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: near Argyle Street railway station | Statement: [Glasgow Cross, proximityToRail, near Argyle Street railway station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: proximityToRail Context triple: [Glasgow Cross, proximityToRail, near Argyle Street railway station]
-
A.
hasNearbyRailway
chosen
Indicates that one entity is located close to a railway associated with or relevant to another entity.
-
B.
distanceToRailhead
Indicates the measured distance between a location or object and the nearest railhead (rail transport access point).
-
C.
isOnRailway
Indicates that one entity is positioned on, aligned with, or traveling along a railway track or railway system in relation to another entity.
-
D.
proximityToRunway
Indicates how close an object or location is to a runway, typically in terms of distance or relative position.
-
E.
distanceFromStation
Indicates the measured spatial separation between an entity and a specified station.
- 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_69e0c4733f4081909a86622e7e6d15d2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f077fede848190b8fe07941d6573d9 |
completed | April 28, 2026, 9:03 a.m. |
| PD | Predicate disambiguation | batch_69e6be751ce881909badced245ef76c7 |
completed | April 21, 2026, 12:01 a.m. |
Created at: April 16, 2026, 6:53 p.m.