Triple
T34879844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louis Washkansky |
E1005981
|
entity |
| Predicate | donorOrganFrom |
P107166
|
FINISHED |
| Object | Denise Darvall |
—
|
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: Denise Darvall | Statement: [Louis Washkansky, donorOrganFrom, Denise Darvall]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: donorOrganFrom Context triple: [Louis Washkansky, donorOrganFrom, Denise Darvall]
-
A.
donorOfTransplantedHeart
chosen
Indicates that one entity is the person who donated a heart that was transplanted into another entity.
-
B.
donorCellSource
Indicates that one entity serves as the originating or contributing donor cell source for another entity or process.
-
C.
donorCellSpecies
Indicates the species from which the donor cell in a biological or experimental context originates.
-
D.
donorOf
Indicates that one entity gives or contributes something (such as resources, organs, or materials) to another entity.
-
E.
organType
Indicates that one entity is classified as a specific type or category of organ in relation to another entity.
- 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_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. |
Created at: May 3, 2026, 4 p.m.