Triple
T20301396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vaxzevria COVID-19 vaccine |
E505486
|
entity |
| Predicate | typicalDoseCount |
P139587
|
FINISHED |
| Object | 2 doses |
—
|
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: 2 doses | Statement: [Vaxzevria COVID-19 vaccine, typicalDoseCount, 2 doses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalDoseCount Context triple: [Vaxzevria COVID-19 vaccine, typicalDoseCount, 2 doses]
-
A.
typicalDosingFrequency
Indicates how often a treatment or medication is usually administered within a standard dosing regimen.
-
B.
hasCommonStartingDose_mgPerDay
Indicates that two treatments share the same typical initial dosage, measured in milligrams per day.
-
C.
typicalDosageCategories
Indicates the standard dosage ranges or categories typically associated with a given treatment, substance, or medication.
-
D.
typicalDosageStyles
Indicates the usual ways or patterns in which a dosage is administered or presented (e.g., standard amounts, frequencies, or formats).
-
E.
maximumDailyDoseTypicalAdult
Indicates the highest amount of a substance that a typical adult is recommended or allowed to take in one day.
- F. None of above. chosen
Provenance (4 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_69e0b4b8ab648190906e18538c250148 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6770c700c81909da247cef0d0f1eb |
completed | April 20, 2026, 6:57 p.m. |
| PD | Predicate disambiguation | batch_69e55b21b09081909e46691b6f45a07f |
completed | April 19, 2026, 10:45 p.m. |
| PDg | Predicate description generation | batch_69e56702ad04819099c1c08f28d16809 |
completed | April 19, 2026, 11:36 p.m. |
Created at: April 16, 2026, 11:17 a.m.