Triple
T6766993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Surrey Fire and Rescue Service |
E154745
|
entity |
| Predicate | emergencyServicesCategory |
P33503
|
FINISHED |
| Object | blue light service |
—
|
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: blue light service | Statement: [Surrey Fire and Rescue Service, emergencyServicesCategory, blue light service]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: emergencyServicesCategory Context triple: [Surrey Fire and Rescue Service, emergencyServicesCategory, blue light service]
-
A.
typeOfEmergencyService
chosen
Indicates the specific category or kind of emergency service associated with or provided in a given situation.
-
B.
emergencyOffice
Indicates that an office or location serves as an emergency contact point or coordination center for urgent or crisis situations.
-
C.
emergencyServicesRegion
Indicates the geographic region within which specific emergency services are responsible for responding to incidents.
-
D.
emergencyDefinitionSection
Indicates a section that defines or explains what constitutes an emergency within a given context or document.
-
E.
hasEmergencyServices
Indicates that the subject provides or is equipped with emergency response services (such as police, fire, or medical assistance).
- 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_69c688109c1c8190added9a221292af0 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2303c6881909405f0d6089dbe12 |
completed | March 27, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69c6d094105881909c5806eb4afa6306 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:12 p.m.