Triple
T7948106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chalfont and Latimer railway station |
E184545
|
entity |
| Predicate | hasBayPlatformFor |
P842
|
FINISHED |
| Object | Chesham shuttle 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: Chesham shuttle services | Statement: [Chalfont and Latimer railway station, hasBayPlatformFor, Chesham shuttle services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBayPlatformFor Context triple: [Chalfont and Latimer railway station, hasBayPlatformFor, Chesham shuttle services]
-
A.
hasBayPlatforms
Indicates that a station or terminal is equipped with bay platforms, where tracks end in a dead-end configuration and trains enter and exit from the same direction.
-
B.
hasPlatformEdge
Indicates that an entity possesses or includes a boundary or edge associated with a platform.
-
C.
hasNotableBay
Indicates that a place possesses a bay that is recognized for its significance, prominence, or special interest.
-
D.
hasNearbyBay
Indicates that one entity is located close to or adjacent to a bay associated with the other entity.
-
E.
hasPlatformType
chosen
Indicates that an entity is associated with or characterized by a specific type or category of 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_69ca8291c2008190b1b8832c87814bcf |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3b2bf6f48190ac7491c41045cab2 |
completed | March 31, 2026, 3:10 a.m. |
| PD | Predicate disambiguation | batch_69cae9361bc48190886b7681e563d46b |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:10 p.m.