Triple
T33626106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Groote Schuur Hospital |
E861409
|
entity |
| Predicate | hasPatientInFirstHeartTransplant |
P199578
|
FINISHED |
| Object | Louis Washkansky |
—
|
NE NERFINISHED |
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: Louis Washkansky | Statement: [Groote Schuur Hospital, hasPatientInFirstHeartTransplant, Louis Washkansky]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPatientInFirstHeartTransplant Context triple: [Groote Schuur Hospital, hasPatientInFirstHeartTransplant, Louis Washkansky]
-
A.
hasDonorInFirstHeartTransplant
Indicates that an entity served as the donor in the first heart transplant involving another entity.
-
B.
hasChiefSurgeonAtTimeOfFirstTransplant
Indicates that a person served as the chief surgeon at the specific time when a particular entity’s first transplant procedure took place.
-
C.
donorOfTransplantedHeart
Indicates that one entity is the person who donated a heart that was transplanted into another entity.
-
D.
receivedBloodTransfusionFrom
Indicates that one entity has been given blood or blood products from another entity through a transfusion procedure.
-
E.
transplantType
Indicates the specific kind of transplant procedure or graft relationship that occurred between entities (e.g., organ, tissue, or cell transplant type).
- F. None of above. chosen
Provenance (4 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_69f34981c54c81909b33c3fa2208a52d |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff46afe7e481908f2862ed11c88db2 |
completed | May 9, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69ff45e9151881909c444a655e852165 |
completed | May 9, 2026, 2:34 p.m. |
| PDg | Predicate description generation | batch_69ff46aefe248190a80d898df6ef1340 |
completed | May 9, 2026, 2:37 p.m. |
Created at: May 1, 2026, 1:41 a.m.