Triple
T23442786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eugene Mirman as Gene Belcher |
E565446
|
entity |
| Predicate | characterAgeRangeInSeries |
P94896
|
FINISHED |
| Object | pre-teen |
—
|
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: pre-teen | Statement: [Eugene Mirman as Gene Belcher, characterAgeRangeInSeries, pre-teen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterAgeRangeInSeries Context triple: [Eugene Mirman as Gene Belcher, characterAgeRangeInSeries, pre-teen]
-
A.
ageInSeries
Indicates the age of an entity as it appears or is depicted within a specific series or installment of a work.
-
B.
hasProtagonistAgeRange
Indicates that a work’s main character falls within a specified age range.
-
C.
portrayedByCharacterAgeApprox
Indicates that an entity is portrayed by a character whose age is approximately a specified value or age range.
-
D.
characterAgeDescriptor
chosen
Indicates how a character’s age is qualitatively described or categorized (e.g., young, middle-aged, elderly) rather than given as a specific number.
-
E.
intendedAudienceOfSeries
Indicates that a particular audience is the primary target or intended recipient of a given series.
- 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_69e24584f9488190bb32730bd2ce023e |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1a64654e88190b530958b27b32412 |
completed | April 29, 2026, 6:33 a.m. |
| PD | Predicate disambiguation | batch_69f061f92da081908e7f1d0cd1e9b01c |
completed | April 28, 2026, 7:30 a.m. |
Created at: April 17, 2026, 5:51 p.m.