Triple
T23250922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Germany’s Next Topmodel |
E581727
|
entity |
| Predicate | typicalContestantAgeRange |
P133912
|
FINISHED |
| Object | late teens to mid-twenties |
—
|
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: late teens to mid-twenties | Statement: [Germany’s Next Topmodel, typicalContestantAgeRange, late teens to mid-twenties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalContestantAgeRange Context triple: [Germany’s Next Topmodel, typicalContestantAgeRange, late teens to mid-twenties]
-
A.
typicalAgeRangeOfPlayers
chosen
Indicates the usual age range of people who typically play or participate in something.
-
B.
typicalAgeRangeOfWinners
Indicates the usual age range within which the winners of a particular competition, award, or event typically fall.
-
C.
ageRange
Indicates the span of ages within which an entity or relationship is considered valid or applicable.
-
D.
typicalAgeOfWinner
Indicates the age that is most commonly observed for entities that win a particular competition, award, or event.
-
E.
hasProtagonistAgeRange
Indicates that a work’s main character falls within a specified age range.
- 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_69e24606b17c81908aba1a4911c8a8ba |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f193f5aa9081909775fb7f7dc660b3 |
completed | April 29, 2026, 5:15 a.m. |
| PD | Predicate disambiguation | batch_69effce4d704819092826931d430e8c4 |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 4:10 p.m.