Triple
T4936783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mabalako |
E110829
|
entity |
| Predicate | hasVaccinationCampaigns |
P58395
|
FINISHED |
| Object | Ebola vaccination campaigns |
—
|
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: Ebola vaccination campaigns | Statement: [Mabalako, hasVaccinationCampaigns, Ebola vaccination campaigns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVaccinationCampaigns Context triple: [Mabalako, hasVaccinationCampaigns, Ebola vaccination campaigns]
-
A.
hasVaccine
Indicates that one entity possesses, provides, or is associated with a specific vaccine in relation to another entity.
-
B.
vaccineUsed
Indicates that a particular vaccine has been administered or applied in a given medical or experimental context.
-
C.
epidemicControlActivities
chosen
Indicates actions or measures undertaken to prevent, contain, or mitigate the spread and impact of an epidemic.
-
D.
conductedCampaignsIn
Indicates that an entity organized or carried out campaigns within a specified location or region.
-
E.
hasDiseaseSurveillance
Indicates that an entity is responsible for or engaged in monitoring, detecting, and tracking the occurrence or spread of diseases in a population or system.
- 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_69bd4415eee08190bdce70276e56a5b4 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd7085b1dc819099408f6503f0210f |
completed | March 20, 2026, 4:06 p.m. |
| PD | Predicate disambiguation | batch_69bd6c389b9881908ad7fb1c5393c1b1 |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:30 p.m.