Triple
T1834670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St Werburgh's Road tram stop |
E41037
|
entity |
| Predicate | hasSidePlatforms |
P33932
|
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: [St Werburgh's Road tram stop, hasSidePlatforms, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSidePlatforms Context triple: [St Werburgh's Road tram stop, hasSidePlatforms, yes]
-
A.
hasNumberOfPlatforms
Indicates the relationship that specifies how many platforms are associated with a given entity.
-
B.
hasIslandPlatforms
Indicates that the subject has one or more island-style platforms, typically positioned between tracks and accessible from both sides.
-
C.
hasShelteredPlatforms
Indicates that the subject provides or includes platforms that are covered or protected from the elements.
-
D.
hasViewingPlatform
Indicates that an entity includes or is equipped with a designated platform or area intended for viewing or observing something.
-
E.
hasTerminatingPlatforms
Indicates that the subject location or facility includes platforms where rail or transit services begin or end their routes, rather than passing through.
- F. None of above. chosen
Provenance (4 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_69a88647f9388190909bc36e795bdaec |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb32d35508190bf1c487dffbecaf0 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abafd88ebc81908208394746351fe6 |
completed | March 7, 2026, 4:55 a.m. |
| PDg | Predicate description generation | batch_69abb32a8d548190a231c7c2ce276a5e |
completed | March 7, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:33 p.m.