Triple
T38251368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 21 Up |
E1014057
|
entity |
| Predicate | depictsAgeOfParticipants |
P108861
|
FINISHED |
| Object | 21 |
—
|
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 | Statement: [21 Up, depictsAgeOfParticipants, 21]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictsAgeOfParticipants Context triple: [21 Up, depictsAgeOfParticipants, 21]
-
A.
portraysAgeGroup
Indicates that one entity depicts or represents another entity as belonging to a particular age group.
-
B.
portraysFromAge
Indicates that one entity depicts another entity starting from a specified age of the depicted entity.
-
C.
ageGroupInvolved
chosen
Indicates that a particular age group participates in, is affected by, or is otherwise involved in the specified event or relationship.
-
D.
depictsAgeContrast
Indicates a relationship where one entity visually represents or highlights a contrast in age between two or more entities.
-
E.
sitterAgeAtTimeOfPortrait
Indicates the age of the sitter at the specific time when the portrait was created or captured.
- 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_69f76dd7e89c8190b7866bc85aea521b |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fdd92396788190ae1424bc1ae55844 |
completed | May 8, 2026, 12:37 p.m. |
| PD | Predicate disambiguation | batch_69fdd678f40481909a717a2daec83b36 |
completed | May 8, 2026, 12:26 p.m. |
Created at: May 3, 2026, 4:30 p.m.