Triple
T23399800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Cunningham virus |
E559471
|
entity |
| Predicate | seroprevalenceInAdults |
P24564
|
FINISHED |
| Object | 50–80 percent |
—
|
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: 50–80 percent | Statement: [John Cunningham virus, seroprevalenceInAdults, 50–80 percent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seroprevalenceInAdults Context triple: [John Cunningham virus, seroprevalenceInAdults, 50–80 percent]
-
A.
hasPrevalence
chosen
Indicates that something occurs or exists at a certain frequency, rate, or proportion within a defined population, group, or context.
-
B.
epidemiologicalStatus
Indicates the health-related condition or disease state of an entity within an epidemiological context, such as being infected, susceptible, recovered, or exposed.
-
C.
preExistingImmunityInHumans
Indicates that humans already possess some level of immune protection against a particular agent, condition, or exposure prior to a specified event or intervention.
-
D.
prevalentIn
Indicates that something occurs frequently or is commonly found within a particular context, group, or environment.
-
E.
experiencedEpidemic
Indicates that an entity has undergone or been affected by an epidemic event.
- 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_69e24549610c8190a069d6411ce5f661 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1a4dedfcc8190ab93cec3c3d15c53 |
completed | April 29, 2026, 6:27 a.m. |
| PD | Predicate disambiguation | batch_69f061dde2e481908308952f9c0d3c2e |
completed | April 28, 2026, 7:29 a.m. |
Created at: April 17, 2026, 5:37 p.m.