Triple
T32354865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Horsforth railway station |
E826705
|
entity |
| Predicate | hasStationBuildings |
P1711
|
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: [Horsforth railway station, hasStationBuildings, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStationBuildings Context triple: [Horsforth railway station, hasStationBuildings, yes]
-
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.
hasTerminalBuildings
Indicates that one entity possesses or includes terminal buildings associated with it.
-
D.
hasMainBuildings
Indicates that one entity possesses or is associated with one or more primary or principal buildings.
-
E.
hasMunicipalBuildings
Indicates that a place or jurisdiction possesses one or more buildings used for municipal or local government functions.
- 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_69f34915a2588190bb3178f5ec2f48f4 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69ff0e9c75208190a4423261f00b79b3 |
completed | May 9, 2026, 10:38 a.m. |
| PD | Predicate disambiguation | batch_69ff0e07f08481909c4ae322632a6bf0 |
completed | May 9, 2026, 10:35 a.m. |
Created at: May 1, 2026, 12:49 a.m.