Triple
T34879850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louis Washkansky |
E1005981
|
entity |
| Predicate | preTransplantCondition |
P181963
|
FINISHED |
| Object | end-stage heart failure |
—
|
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: end-stage heart failure | Statement: [Louis Washkansky, preTransplantCondition, end-stage heart failure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: preTransplantCondition Context triple: [Louis Washkansky, preTransplantCondition, end-stage heart failure]
-
A.
returnedToPlayAfterTransplant
Indicates that an individual resumed participating in play or sport following a transplant procedure.
-
B.
hasDonorInFirstHeartTransplant
Indicates that an entity served as the donor in the first heart transplant involving another entity.
-
C.
receivedBloodTransfusionFrom
Indicates that one entity has been given blood or blood products from another entity through a transfusion procedure.
-
D.
donorOfTransplantedHeart
Indicates that one entity is the person who donated a heart that was transplanted into another entity.
-
E.
precondition
Indicates that one event, state, or condition must be true or occur before another event, state, or condition can validly or successfully take place.
- 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_69f76dbde1c08190a24e7f9beb564c8d |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f782f4f10081908f97f6d0d2dbeec7 |
completed | May 3, 2026, 5:16 p.m. |
| PD | Predicate disambiguation | batch_69f780ff71cc8190a67e71076fbad81a |
completed | May 3, 2026, 5:08 p.m. |
| PDg | Predicate description generation | batch_69f782f416c081908bdd9b1ad456f0e2 |
completed | May 3, 2026, 5:16 p.m. |
Created at: May 3, 2026, 4 p.m.