Triple
T25833952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sandy Spring Volunteer Fire Department Station in Olney |
E650742
|
entity |
| Predicate | hasVolunteerFirefighters |
P62810
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Sandy Spring Volunteer Fire Department Station in Olney, hasVolunteerFirefighters, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVolunteerFirefighters Context triple: [Sandy Spring Volunteer Fire Department Station in Olney, hasVolunteerFirefighters, true]
-
A.
hasFireRescueService
Indicates that an entity is served by, or responsible for providing, a fire and rescue service.
-
B.
hasFireServicesFrom
chosen
Indicates that one entity receives fire protection or firefighting services from another entity.
-
C.
hasRuralFireServiceBrigade
Indicates that a specified area or jurisdiction is served by a particular rural fire service brigade.
-
D.
numberOfFirefightersInvolved
Indicates the total count of firefighters who participated in or were involved in a specific event, incident, or operation.
-
E.
hasVolunteerPersonnelFrom
Indicates that an entity receives or utilizes volunteer personnel supplied by another entity or source.
- 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_69e7ab37438081908f1ccf6284839520 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f638d11c988190af7fd4572b08e038 |
completed | May 2, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69f63706b6008190993577193c85ff50 |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 22, 2026, 7:40 a.m.