Triple
T6955660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Memorial Regional Hospital |
E161235
|
entity |
| Predicate | hasSurgicalICU |
P29662
|
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: [Memorial Regional Hospital, hasSurgicalICU, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSurgicalICU Context triple: [Memorial Regional Hospital, hasSurgicalICU, yes]
-
A.
hasIntensiveCareUnit
chosen
Indicates that a medical facility includes and operates an intensive care unit (ICU) for critically ill patients.
-
B.
hasSurgery
Indicates that a surgical procedure is performed on or undergone by an entity.
-
C.
neonatalICULevel
Indicates the level or tier of care provided by a neonatal intensive care unit (NICU) in relation to the newborn patient.
-
D.
hasICD10Code
Indicates that an entity is associated with a specific ICD-10 diagnostic code used for classifying diseases and health conditions.
-
E.
surgicalField
Indicates the specific anatomical area or region of the body on which a surgical procedure is performed.
- 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_69c68852a9a0819097797e31d492e273 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dacf8c8c8190a25dbacebeb4b66e |
completed | March 27, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69c6d7bf0a7c8190b5ed4aca22ba9b97 |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:29 p.m.