Triple
T21465813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American black-footed ferret |
E529590
|
entity |
| Predicate | majorDisease |
P40194
|
FINISHED |
| Object | sylvatic plague |
—
|
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: sylvatic plague | Statement: [American black-footed ferret, majorDisease, sylvatic plague]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorDisease Context triple: [American black-footed ferret, majorDisease, sylvatic plague]
-
A.
diseaseType
Indicates that one entity is classified as a specific type or category of disease in relation to another entity.
-
B.
humanDisease
Indicates that the subject is a disease that affects humans.
-
C.
primaryDisease
chosen
Indicates that a disease is the main or principal medical condition affecting an entity, as opposed to secondary or comorbid conditions.
-
D.
hasAssociatedDisease
Indicates that an entity is linked to, or commonly occurs with, a particular disease or medical condition.
-
E.
illness
Indicates that an entity is affected by, or suffering from, a particular disease or medical condition.
- 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_69e0c458133481908ae8b41a12c4edec |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9e9f1b3cc819092c200f09c6f461e |
completed | April 23, 2026, 9:44 a.m. |
| PD | Predicate disambiguation | batch_69e631ec1d048190b6da97da8222e413 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:09 p.m.