Triple
T15377760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joel Miller (TV series character) |
E367712
|
entity |
| Predicate | ageDuringMainStory |
P94404
|
FINISHED |
| Object | late 40s to early 50s (approximate) |
—
|
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 40s to early 50s (approximate) | Statement: [Joel Miller (TV series character), ageDuringMainStory, late 40s to early 50s (approximate)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageDuringMainStory Context triple: [Joel Miller (TV series character), ageDuringMainStory, late 40s to early 50s (approximate)]
-
A.
ageDuringNarration
Indicates that an entity has a specified age at the time when the described narrative or event is taking place.
-
B.
ageDuringMainEvents
chosen
Indicates the age an entity has at the time when the main events of a referenced context or narrative occur.
-
C.
protagonistAge
Indicates the age of the main character or central figure in a narrative or scenario.
-
D.
ageInSeries
Indicates the age of an entity as it appears or is depicted within a specific series or installment of a work.
-
E.
ageInPlay
Indicates that an entity’s age is relevant or applicable within the context of a particular play, game, or interactive scenario.
- 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_69d85a1551a08190ba2caea7cd51c639 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e5ece1081908d7c1289258b9c1f |
completed | April 16, 2026, 1:41 a.m. |
| PD | Predicate disambiguation | batch_69ded27742a881909cd73cc5c7d062fd |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:18 a.m.