Triple
T33314794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Highland Park Fire Department |
E852984
|
entity |
| Predicate | incidentTypeHandled |
P76024
|
FINISHED |
| Object | structure fires |
—
|
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: structure fires | Statement: [Highland Park Fire Department, incidentTypeHandled, structure fires]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: incidentTypeHandled Context triple: [Highland Park Fire Department, incidentTypeHandled, structure fires]
-
A.
incidentWith
Indicates that one entity is involved in, affected by, or associated with a particular incident or event together with another entity.
-
B.
incidentName
Indicates the specific name or label assigned to an incident within a system or context.
-
C.
commonIncidentType
Indicates that multiple entities share the same category or type of incident.
-
D.
incidentDescription
Indicates a textual explanation or narrative detailing the circumstances, events, and relevant facts associated with a particular incident.
-
E.
notableIncidentType
chosen
Indicates the specific category or kind of significant event or incident associated with an 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_69f349679fd8819093b9b40e989440e3 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6e3156ea48190b604e414665ef351 |
completed | May 3, 2026, 5:54 a.m. |
| PD | Predicate disambiguation | batch_69f6de0b9ba48190887c9eb5d06a2e94 |
completed | May 3, 2026, 5:32 a.m. |
Created at: May 1, 2026, 1:33 a.m.