Triple
T31625250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Altnagelvin Area Hospital |
E807003
|
entity |
| Predicate | hasEmergencySurgery |
P172032
|
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: [Altnagelvin Area Hospital, hasEmergencySurgery, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEmergencySurgery Context triple: [Altnagelvin Area Hospital, hasEmergencySurgery, yes]
-
A.
hasEmergencyCare
Indicates that an entity provides or is equipped with emergency medical care services for another entity or individuals.
-
B.
hasSurgery
Indicates that a surgical procedure is performed on or undergone by an entity.
-
C.
hasEmergencyDepartmentLevel
Indicates the specific classification or tier of emergency care capability associated with an emergency department.
-
D.
hasEmergencyTransport
Indicates that an entity provides, is equipped with, or has access to emergency transportation services or vehicles.
-
E.
hasEmergencyServiceProvider
Indicates that an entity is associated with or served by a specific emergency service provider (such as police, fire, or medical services).
- 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_69f348d7883c8190b6c13ab92b7ef076 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a956e9b08190bf83547bba8e8147 |
completed | May 3, 2026, 1:48 a.m. |
| PD | Predicate disambiguation | batch_69f6a757c6e081908e37631e5d8d246b |
completed | May 3, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f6a8036ab481908019f2f071fa406e |
completed | May 3, 2026, 1:42 a.m. |
Created at: April 30, 2026, 10:43 p.m.