Triple
T25143578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CHU Sainte-Justine |
E629869
|
entity |
| Predicate | hasPediatricIntensiveCareUnit |
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: [CHU Sainte-Justine, hasPediatricIntensiveCareUnit, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPediatricIntensiveCareUnit Context triple: [CHU Sainte-Justine, hasPediatricIntensiveCareUnit, yes]
-
A.
hasIntensiveCareUnit
chosen
Indicates that a medical facility includes and operates an intensive care unit (ICU) for critically ill patients.
-
B.
hasPediatricHospital
Indicates that an entity possesses or is associated with a hospital facility that provides medical services specifically for children.
-
C.
hasCardiacCareUnit
Indicates that an entity (such as a hospital or medical facility) includes or is equipped with a specialized cardiac care unit for treating heart-related conditions.
-
D.
neonatalICULevel
Indicates the level or tier of care provided by a neonatal intensive care unit (NICU) in relation to the newborn patient.
-
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_69e2ff349e408190a6f4a5a66279f54d |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f5ffc74fa481909b4fe24a9337f9eb |
completed | May 2, 2026, 1:44 p.m. |
| PD | Predicate disambiguation | batch_69f5f7f99dc08190afcfb3bc4dfbec1d |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 18, 2026, 6:29 a.m.