Triple
T6766730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frimley Park Hospital |
E154737
|
entity |
| Predicate | hasNeonatalUnit |
P64825
|
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: [Frimley Park Hospital, hasNeonatalUnit, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNeonatalUnit Context triple: [Frimley Park Hospital, hasNeonatalUnit, yes]
-
A.
hasIntensiveCareUnit
Indicates that a medical facility includes and operates an intensive care unit (ICU) for critically ill patients.
-
B.
neonatalICULevel
chosen
Indicates the level or tier of care provided by a neonatal intensive care unit (NICU) in relation to the newborn patient.
-
C.
containsHospital
Indicates that one entity includes or encompasses a hospital within its boundaries or composition.
-
D.
hasNurse
Indicates that an entity is assigned or associated with a nurse who provides care or medical support to it.
-
E.
hospitalizedIn
Indicates that a person or patient is admitted for medical care and staying as an inpatient in a specified hospital or healthcare facility.
- 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_69c688109c1c8190added9a221292af0 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2303c6881909405f0d6089dbe12 |
completed | March 27, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69c6d094105881909c5806eb4afa6306 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:12 p.m.