Triple
T7040867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shelford railway station |
E163505
|
entity |
| Predicate | hasStationBuildingType |
P1711
|
FINISHED |
| Object | suburban railway stop |
—
|
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 railway stop | Statement: [Shelford railway station, hasStationBuildingType, suburban railway stop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStationBuildingType Context triple: [Shelford railway station, hasStationBuildingType, suburban railway stop]
-
A.
hasStationBuilding
chosen
Indicates that a station is associated with or includes a station building as part of its facilities.
-
B.
hasStationBuildingMaterial
Indicates that a station’s building is constructed from, or primarily composed of, a specified material.
-
C.
containsBuildingType
Indicates that a location or area includes at least one building of the specified type.
-
D.
hasStationStructure
Indicates that an entity possesses or is associated with a particular station-related physical structure.
-
E.
hasStationHall
Indicates that one entity (typically a station) includes or is associated with a station hall area as part of its structure or facilities.
- 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_69c6885e7c1c8190be32a8f79ab4e0cf |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e4a3c36c819080942c59f1830ae8 |
completed | March 27, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69c6e1bb602081908bfa6186a1f5a4b4 |
completed | March 27, 2026, 7:59 p.m. |
Created at: March 27, 2026, 2:36 p.m.