Triple
T4132102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | rVSV-ZEBOV |
E85063
|
entity |
| Predicate | regimen |
P37228
|
FINISHED |
| Object | single-dose vaccination |
—
|
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: single-dose vaccination | Statement: [rVSV-ZEBOV, regimen, single-dose vaccination]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regimen Context triple: [rVSV-ZEBOV, regimen, single-dose vaccination]
-
A.
doseRegimen
chosen
Indicates the specific schedule, frequency, and amount with which a dose of a substance or medication is to be administered.
-
B.
belongsToRegimen
Indicates that something is a component or member of a specified regimen or structured treatment plan.
-
C.
hasDosingRegimen
Indicates that an entity is associated with a specific dosing regimen, defining how and when a dose is to be administered.
-
D.
regimeServed
Indicates that an entity (typically a person or organization) served under, worked for, or was aligned with a particular political or governing regime.
-
E.
remedy
Indicates that one entity serves to cure, alleviate, or counteract a problem, illness, or undesirable condition affecting 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_69aed935ccd881909dc61f81bcdb7a78 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af03a0f3408190adba7a8513bd3d12 |
completed | March 9, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69af01883b6c8190a482ead589a131a5 |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:42 p.m.