Triple
T11386043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baby Looney Tunes |
E269716
|
entity |
| Predicate | characterAgeDepiction |
P13483
|
FINISHED |
| Object | toddlers |
—
|
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: toddlers | Statement: [Baby Looney Tunes, characterAgeDepiction, toddlers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterAgeDepiction Context triple: [Baby Looney Tunes, characterAgeDepiction, toddlers]
-
A.
characterAgeDescriptor
Indicates how a character’s age is qualitatively described or categorized (e.g., young, middle-aged, elderly) rather than given as a specific number.
-
B.
portrayedByCharacterAgeApprox
Indicates that an entity is portrayed by a character whose age is approximately a specified value or age range.
-
C.
portraysAgeGroup
chosen
Indicates that one entity depicts or represents another entity as belonging to a particular age group.
-
D.
isAdultCharacter
Indicates that a character has reached adulthood, typically meeting the age or maturity criteria defining an adult within the given context.
-
E.
representedAgeLevel
Indicates that one entity corresponds to, or is categorized under, a particular age level or age group.
- 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_69d6aacdbc6c8190af6dc3d5f5d22836 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d800160a1c81909d115bf89fe54a49 |
completed | April 9, 2026, 7:37 p.m. |
| PD | Predicate disambiguation | batch_69d7e70b228c8190b87f5101fd683788 |
completed | April 9, 2026, 5:51 p.m. |
Created at: April 8, 2026, 9:34 p.m.