Triple
T31818463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BNT162b2 |
E812198
|
entity |
| Predicate | hasAgeIndication |
P125218
|
FINISHED |
| Object | adults |
—
|
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: adults | Statement: [BNT162b2, hasAgeIndication, adults]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAgeIndication Context triple: [BNT162b2, hasAgeIndication, adults]
-
A.
hasAge
Indicates that an entity possesses a specific age value, typically expressed as a number of time units since its birth or creation.
-
B.
containsAge
Indicates that one entity includes or specifies the age value or age-related information of another entity.
-
C.
hasAgeSignificance
Indicates that something holds particular importance, relevance, or meaning specifically due to its age or the age of an associated entity.
-
D.
hasApproximateAgeRange
Indicates that one entity is associated with another entity representing an estimated or non-exact span of ages.
-
E.
ageGroupIndicated
chosen
Indicates that a specific age range or category is identified or assigned to an 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_69f348e846c081908eb468a0665afd55 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6af7f24a881909e6ae0d937e90ea2 |
completed | May 3, 2026, 2:14 a.m. |
| PD | Predicate disambiguation | batch_69f6aca59d4881908d14ed47962703bd |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 30, 2026, 11:45 p.m.