Triple
T23570498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SECAmb |
E580091
|
entity |
| Predicate | hasAmbulanceStations |
P83367
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [SECAmb, hasAmbulanceStations, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAmbulanceStations Context triple: [SECAmb, hasAmbulanceStations, yes]
-
A.
hasAidStations
Indicates that one entity provides or contains aid or support stations for another entity or within a specified context.
-
B.
hasPoliceStationsIn
Indicates that one entity possesses, manages, or contains one or more police stations located within the area or jurisdiction of another entity.
-
C.
hasFireStation
Indicates that a location or area contains or is served by a fire station.
-
D.
hasStations
chosen
Indicates that one entity possesses, contains, or is associated with one or more stations.
-
E.
hasTraumaCenter
Indicates that an entity (such as a hospital or facility) includes or is equipped with a designated trauma center capable of providing specialized emergency care for severe injuries.
- 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_69e24601a9108190bc31e83833c980e4 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1afd259e4819094b09f3ed76664ea |
completed | April 29, 2026, 7:14 a.m. |
| PD | Predicate disambiguation | batch_69f118bcc0b08190b25a8dddfd461a0e |
completed | April 28, 2026, 8:29 p.m. |
Created at: April 17, 2026, 6:36 p.m.