Triple
T33974905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RHINE |
E871107
|
entity |
| Predicate | enrollsPatientsWith |
P35131
|
FINISHED |
| Object | center-involved diabetic macular edema |
—
|
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: center-involved diabetic macular edema | Statement: [RHINE, enrollsPatientsWith, center-involved diabetic macular edema]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: enrollsPatientsWith Context triple: [RHINE, enrollsPatientsWith, center-involved diabetic macular edema]
-
A.
hasPatient
Indicates that an action, event, or process involves a specific entity as the one undergoing or receiving its effects (the patient).
-
B.
isUsedForPatients
Indicates that something is employed or applied in the care, treatment, or management of patients.
-
C.
hasPatientGroup
chosen
Indicates a relationship in which an entity (such as a study, treatment, or clinical activity) is associated with a specific group of patients it involves or targets.
-
D.
treatsPatientsFrom
Indicates that a healthcare provider gives medical treatment or services to patients originating from a particular location or group.
-
E.
openedForPatients
Indicates that a healthcare facility or service is currently available and accepting patients for care or treatment.
- 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_69f3499da0188190ab1a4ff06fb06a2a |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7064e906881909c3186c646145d34 |
completed | May 3, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_69f70100ec1c8190a6b97f50e88891f2 |
completed | May 3, 2026, 8:02 a.m. |
Created at: May 1, 2026, 1:50 a.m.