Triple
T7357479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yorkshire Ambulance Service |
E169660
|
entity |
| Predicate | hasNonEmergencyNumber |
P77037
|
FINISHED |
| Object | 111 |
—
|
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: 111 | Statement: [Yorkshire Ambulance Service, hasNonEmergencyNumber, 111]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNonEmergencyNumber Context triple: [Yorkshire Ambulance Service, hasNonEmergencyNumber, 111]
-
A.
operatesNonEmergencyNumber
Indicates that an entity is responsible for running or managing a telephone number designated for non-emergency inquiries or services.
-
B.
usesEmergencyNumber
Indicates that an entity initiates contact or communication by dialing or otherwise employing an officially designated emergency telephone number.
-
C.
emergencyPhoneNumber
Indicates that the object is a phone number designated for use in emergencies or urgent situations.
-
D.
hasEmergencyServices
Indicates that the subject provides or is equipped with emergency response services (such as police, fire, or medical assistance).
-
E.
hasTelephoneService
Indicates that a subject is provided with or connected to telephone service.
- F. None of above. chosen
Provenance (4 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_69c68a59f2288190877ca15c19b1e822 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f26d6d6081909c7272a9ccae0d97 |
completed | March 27, 2026, 9:11 p.m. |
| PD | Predicate disambiguation | batch_69c6f02d36108190bcb34a95e6a30bd7 |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f26c050c8190a2d009b45d920490 |
completed | March 27, 2026, 9:11 p.m. |
Created at: March 27, 2026, 3:06 p.m.