Triple
T36398408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joshua Cody |
E896550
|
entity |
| Predicate | characterAgeAtSeriesStart |
P59141
|
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: [Joshua Cody, characterAgeAtSeriesStart, teenager]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterAgeAtSeriesStart Context triple: [Joshua Cody, characterAgeAtSeriesStart, teenager]
-
A.
ageInSeries
chosen
Indicates the age of an entity as it appears or is depicted within a specific series or installment of a work.
-
B.
portrayedByCharacterAgeApprox
Indicates that an entity is portrayed by a character whose age is approximately a specified value or age range.
-
C.
protagonistAge
Indicates the age of the main character or central figure in a narrative or scenario.
-
D.
ageInFirstAppearance
Indicates the age an entity was when it first appeared or was initially introduced in a given context.
-
E.
ageDuringNarration
Indicates that an entity has a specified age at the time when the described narrative or event is taking place.
- 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_69f76e53b81081908d3b81860593f38a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ffb82be8148190a1c870d467a28c80 |
completed | May 9, 2026, 10:41 p.m. |
| PD | Predicate disambiguation | batch_69ffb7bbd550819094052e9a0d0ae320 |
completed | May 9, 2026, 10:39 p.m. |
Created at: May 3, 2026, 4:10 p.m.