Triple
T10858523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manchester University NHS Foundation Trust |
E256331
|
entity |
| Predicate | operatesEmergencyDepartment |
P59476
|
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: [Manchester University NHS Foundation Trust, operatesEmergencyDepartment, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatesEmergencyDepartment Context triple: [Manchester University NHS Foundation Trust, operatesEmergencyDepartment, yes]
-
A.
emergencyDepartment
Indicates that an entity is associated with, located in, or functions as an emergency department within a healthcare or medical context.
-
B.
operatesTheatre
Indicates that an entity manages and runs the activities of a theatre.
-
C.
emergencyOffice
Indicates that an office or location serves as an emergency contact point or coordination center for urgent or crisis situations.
-
D.
hasEmergencyCare
chosen
Indicates that an entity provides or is equipped with emergency medical care services for another entity or individuals.
-
E.
emergencyCareLevel
Indicates the degree or intensity of medical attention required in an emergency situation.
- 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_69d6aa83d1448190a66d93c32394d21f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d751500e248190823a16f2c85ad829 |
completed | April 9, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69d70d308dfc81908792f98cfb871392 |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:20 p.m.