Triple
T13948035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doogie Howser, M.D. |
E335441
|
entity |
| Predicate | mainCharacterAgeCategory |
P71516
|
FINISHED |
| Object | teenager |
—
|
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: teenager | Statement: [Doogie Howser, M.D., mainCharacterAgeCategory, teenager]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainCharacterAgeCategory Context triple: [Doogie Howser, M.D., mainCharacterAgeCategory, teenager]
-
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.
protagonistAge
Indicates the age of the main character or central figure in a narrative or scenario.
-
C.
representedAgeLevel
chosen
Indicates that one entity corresponds to, or is categorized under, a particular age level or age group.
-
D.
mainProtagonist
Indicates that the subject is the central character or primary focus in the narrative of the related work.
-
E.
isAdultCharacter
Indicates that a character has reached adulthood, typically meeting the age or maturity criteria defining an adult within the given context.
- 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_69d81c6081b88190b53e317c3370c8fe |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e12171c8190b95746bdd4845def |
completed | April 14, 2026, 12:07 p.m. |
| PD | Predicate disambiguation | batch_69de05a3ccf88190b45c742db483fa08 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:17 p.m.