Triple
T24392935
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northern Ireland Fire and Rescue Service |
E614946
|
entity |
| Predicate | numberOfFireStations |
P1301
|
FINISHED |
| Object | approximately 68 |
—
|
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: approximately 68 | Statement: [Northern Ireland Fire and Rescue Service, numberOfFireStations, approximately 68]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfFireStations Context triple: [Northern Ireland Fire and Rescue Service, numberOfFireStations, approximately 68]
-
A.
hasFireStation
Indicates that a location or area contains or is served by a fire station.
-
B.
numberOfStations
chosen
Indicates the total count of stations associated with or contained by a given entity.
-
C.
numberOfFirefightersInvolved
Indicates the total count of firefighters who participated in or were involved in a specific event, incident, or operation.
-
D.
hasFireServicesFrom
Indicates that one entity receives fire protection or firefighting services from another entity.
-
E.
numberOfUndergroundStations
Indicates the total count of underground (subway/metro) stations associated with a given entity.
- 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_69e2d7e509b88190a53155d4f3de45ce |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2945a2f6c8190b11a027c446ffe34 |
completed | April 29, 2026, 11:29 p.m. |
| PD | Predicate disambiguation | batch_69f287c4a2b48190b80fb7a3c0e9b018 |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 2:04 a.m.