Triple
T33899768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St Andrew Square, Edinburgh |
E869013
|
entity |
| Predicate | hasRailConnectionNearby |
P170255
|
FINISHED |
| Object | Edinburgh Waverley railway station |
—
|
NE NERFINISHED |
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: Edinburgh Waverley railway station | Statement: [St Andrew Square, Edinburgh, hasRailConnectionNearby, Edinburgh Waverley railway station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRailConnectionNearby Context triple: [St Andrew Square, Edinburgh, hasRailConnectionNearby, Edinburgh Waverley railway station]
-
A.
hasNearbyRailway
Indicates that one entity is located close to a railway associated with or relevant to another entity.
-
B.
connectsToRailStation
Indicates that one entity has a direct link, route, or access connection to a rail station.
-
C.
hasRailStation
Indicates that one entity possesses, contains, or is served by a rail station.
-
D.
railConnectionNearby
chosen
Indicates that there is a railway connection located close to the referenced entity or location.
-
E.
connectsToRailwayNetwork
Indicates that one entity is physically or functionally linked to a railway network, allowing access or transfer between them.
- 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_69f34997703c8190866b1d404bce531f |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fcf1b3d9a08190850b388308656266 |
completed | May 7, 2026, 8:10 p.m. |
| PD | Predicate disambiguation | batch_69fcf0226d8c8190b23dceafb1794995 |
completed | May 7, 2026, 8:03 p.m. |
Created at: May 1, 2026, 1:48 a.m.