Triple
T306301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Newton Fire Department |
E6309
|
entity |
| Predicate | emergencyNumber |
P5467
|
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: [Newton Fire Department, emergencyNumber, 911]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: emergencyNumber Context triple: [Newton Fire Department, emergencyNumber, 911]
-
A.
emergencyOffice
Indicates that an office or location serves as an emergency contact point or coordination center for urgent or crisis situations.
-
B.
emergencyPower
Indicates that an entity has backup or auxiliary power available or activated for use during emergencies or primary power failures.
-
C.
hasEmergencyServices
Indicates that the subject provides or is equipped with emergency response services (such as police, fire, or medical assistance).
-
D.
callingCode
Indicates the telephone country or area code associated with an entity for making phone calls.
-
E.
associatedNumber
chosen
Indicates a relationship where a specific number is linked or assigned to an entity as its associated value.
- 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_69a2e79230508190b912ecb555aae17e |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea2fba548190a5aeb1597dca96bd |
completed | Feb. 28, 2026, 1:14 p.m. |
| PD | Predicate disambiguation | batch_69a2e93db11881909b07ba5e76d91feb |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:06 p.m.