Triple
T6690232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chertsey railway station |
E152604
|
entity |
| Predicate | hasPlatformsUsage |
P39701
|
FINISHED |
| Object | suburban stopping services |
—
|
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: suburban stopping services | Statement: [Chertsey railway station, hasPlatformsUsage, suburban stopping services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlatformsUsage Context triple: [Chertsey railway station, hasPlatformsUsage, suburban stopping services]
-
A.
platformUsage
chosen
Indicates how an entity uses, engages with, or relies on a particular platform for its activities or services.
-
B.
hasNumberOfPlatforms
Indicates the relationship that specifies how many platforms are associated with a given entity.
-
C.
hasPrimaryPlatform
Indicates that one entity is designated as the main or principal platform associated with another entity.
-
D.
platformUsed
Indicates that an action, event, or interaction was carried out using a particular platform (e.g., software, service, or system) as the medium or tool.
-
E.
supportedPlatform
Indicates that one entity (such as a system, application, or service) is compatible with and can operate on a particular platform.
- 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_69c6880687b08190805278b504d1c92c |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6cd0fa5188190a23281cb09d98139 |
completed | March 27, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69c6ad0d3c1081908dadff7a6a054123 |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:04 p.m.