Triple
T34879837
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louis Washkansky |
E1005981
|
entity |
| Predicate | numberOfDaysSurvivedAfterTransplant |
P205593
|
FINISHED |
| Object | 18 |
—
|
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: 18 | Statement: [Louis Washkansky, numberOfDaysSurvivedAfterTransplant, 18]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfDaysSurvivedAfterTransplant Context triple: [Louis Washkansky, numberOfDaysSurvivedAfterTransplant, 18]
-
A.
returnedToPlayAfterTransplant
Indicates that an individual resumed participating in play or sport following a transplant procedure.
-
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.
transplantType
Indicates the specific kind of transplant procedure or graft relationship that occurred between entities (e.g., organ, tissue, or cell transplant type).
-
D.
hasPatientInFirstHeartTransplant
Indicates that the subject is the patient involved in the first heart transplant procedure performed by the object.
-
E.
donorOfTransplantedHeart
Indicates that one entity is the person who donated a heart that was transplanted into another entity.
- 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_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379ff1ba081908eda86acefcf69fb |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4 p.m.