Triple
T11272703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aegidienberg |
E266851
|
entity |
| Predicate | hasFireBrigade |
P44903
|
FINISHED |
| Object | volunteer fire brigade |
—
|
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: volunteer fire brigade | Statement: [Aegidienberg, hasFireBrigade, volunteer fire brigade]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFireBrigade Context triple: [Aegidienberg, hasFireBrigade, volunteer fire brigade]
-
A.
hasFireServicesFrom
Indicates that one entity receives fire protection or firefighting services from another entity.
-
B.
hasFireStation
chosen
Indicates that a location or area contains or is served by a fire station.
-
C.
hasFireAndRescueServiceCategory
Indicates the specific fire and rescue service classification or category assigned to an entity, such as a building, facility, or site.
-
D.
fireRescue
Indicates a relationship where one entity performs or is responsible for rescuing people or property from fires or fire-related emergencies involving another entity.
-
E.
hasFireServiceCollege
Indicates that an entity is associated with, or has jurisdiction over, a specific fire service training or educational college.
- 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_69d6aac8c2f48190ad0596f1f89f0470 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e965c9048190804ebb48f0a4817b |
completed | April 9, 2026, 6:01 p.m. |
| PD | Predicate disambiguation | batch_69d7879bc56c8190b2e8d2193f29de05 |
completed | April 9, 2026, 11:03 a.m. |
Created at: April 8, 2026, 9:31 p.m.