Triple
T1318106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belton Fire Department |
E28152
|
entity |
| Predicate | emergencyTelephoneNumber |
P21774
|
FINISHED |
| Object | 911 |
—
|
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: 911 | Statement: [Belton Fire Department, emergencyTelephoneNumber, 911]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: emergencyTelephoneNumber Context triple: [Belton Fire Department, emergencyTelephoneNumber, 911]
-
A.
usesEmergencyNumber
chosen
Indicates that an entity initiates contact or communication by dialing or otherwise employing an officially designated emergency telephone number.
-
B.
emergencyOffice
Indicates that an office or location serves as an emergency contact point or coordination center for urgent or crisis situations.
-
C.
associatedNumber
Indicates a relationship where a specific number is linked or assigned to an entity as its associated value.
-
D.
hasEmergencyServices
Indicates that the subject provides or is equipped with emergency response services (such as police, fire, or medical assistance).
-
E.
officeNumber
Indicates the specific room or suite number assigned to an office within a building or complex.
- 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_69a498532c3481909223b74af2e578df |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c176c89881909e9dc0e34f12f056 |
completed | March 1, 2026, 10:45 p.m. |
| PD | Predicate disambiguation | batch_69a4beebcb348190964bd7215811942c |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:55 p.m.