Triple
T31818448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BNT162b2 |
E812198
|
entity |
| Predicate | hasDoseInterval |
P26891
|
FINISHED |
| Object | 21 days between first and second dose |
—
|
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: 21 days between first and second dose | Statement: [BNT162b2, hasDoseInterval, 21 days between first and second dose]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDoseInterval Context triple: [BNT162b2, hasDoseInterval, 21 days between first and second dose]
-
A.
dosingInterval
chosen
Indicates the time period that should elapse between consecutive doses of a medication or treatment.
-
B.
hasDosingRegimen
Indicates that an entity is associated with a specific dosing regimen, defining how and when a dose is to be administered.
-
C.
hasDefinedDailyDose
Indicates that an entity has an established standard amount intended to be taken or used per day.
-
D.
typicalDosingFrequency
Indicates how often a treatment or medication is usually administered within a standard dosing regimen.
-
E.
hasDosingBasis
Indicates that one dosing specification is based on, derived from, or determined according to another dosing-related parameter or standard.
- 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_69f348e846c081908eb468a0665afd55 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f71996e1a48190ac59a1d66d7c44e8 |
completed | May 3, 2026, 9:47 a.m. |
| PD | Predicate disambiguation | batch_69f71820c6c88190ab38b4fa626d22cc |
completed | May 3, 2026, 9:40 a.m. |
Created at: April 30, 2026, 11:45 p.m.