Triple
T5824320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Castleton railway station |
E129183
|
entity |
| Predicate | hasEmergencyContactFacilities |
P9116
|
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: [Castleton railway station, hasEmergencyContactFacilities, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEmergencyContactFacilities Context triple: [Castleton railway station, hasEmergencyContactFacilities, yes]
-
A.
hasEmergencyCare
Indicates that an entity provides or is equipped with emergency medical care services for another entity or individuals.
-
B.
hasEmergencyServices
Indicates that the subject provides or is equipped with emergency response services (such as police, fire, or medical assistance).
-
C.
hasMaintenanceFacilities
Indicates that one entity provides or contains facilities where the other entity can be serviced, repaired, or maintained.
-
D.
hasFacilities
Indicates that an entity possesses, provides, or is equipped with certain facilities or physical resources.
-
E.
emergencyOffice
chosen
Indicates that an office or location serves as an emergency contact point or coordination center for urgent or crisis situations.
- 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_69c00849d55481908b4f9f5543e0bf6d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0400f1af881908d376ea4793f6dea |
completed | March 22, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69c0333fdd7081908d829265caa2ac11 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:53 p.m.