Triple
T32524109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | COVID-19 pandemic in Belgium |
E831261
|
entity |
| Predicate | vaccinesUsed |
P18429
|
FINISHED |
| Object | Pfizer–BioNTech COVID-19 vaccine |
—
|
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: Pfizer–BioNTech COVID-19 vaccine | Statement: [COVID-19 pandemic in Belgium, vaccinesUsed, Pfizer–BioNTech COVID-19 vaccine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vaccinesUsed Context triple: [COVID-19 pandemic in Belgium, vaccinesUsed, Pfizer–BioNTech COVID-19 vaccine]
-
A.
vaccineUsed
chosen
Indicates that a particular vaccine has been administered or applied in a given medical or experimental context.
-
B.
vaccineTypeUsed
Indicates that a specific type or category of vaccine was administered or employed in a vaccination event or context.
-
C.
developedVaccineFor
Indicates that one entity created or produced a vaccine intended to prevent or protect against a disease or condition associated with another entity.
-
D.
testedVaccineOn
Indicates that one entity conducted tests or experiments using another entity as the vaccine subject.
-
E.
hasVaccine
Indicates that one entity possesses, provides, or is associated with a specific vaccine 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_69f34923e1548190be0524205d8cdf8f |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6cd126fcc8190aa1f1f146e45ec0c |
completed | May 3, 2026, 4:20 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1470808190b70cdfd7a6395670 |
completed | May 3, 2026, 4:16 a.m. |
Created at: May 1, 2026, 1:01 a.m.