Triple
T32252507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Granny – Irene Ryan |
E823919
|
entity |
| Predicate | agePortrayal |
P161441
|
FINISHED |
| Object | elderly |
—
|
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: elderly | Statement: [Granny – Irene Ryan, agePortrayal, elderly]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: agePortrayal Context triple: [Granny – Irene Ryan, agePortrayal, elderly]
-
A.
portrayalAge
chosen
Indicates the age or life stage at which an entity is depicted or represented in a given context.
-
B.
portraysFromAge
Indicates that one entity depicts another entity starting from a specified age of the depicted entity.
-
C.
portraysAgeGroup
Indicates that one entity depicts or represents another entity as belonging to a particular age group.
-
D.
wasPortrayedAs
Indicates that one entity has been depicted or represented in the form or role of another entity, typically within some medium or context.
-
E.
portrayedByCharacterAgeApprox
Indicates that an entity is portrayed by a character whose age is approximately a specified value or age range.
- 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_69f3490db0748190bfef6e50c95d39d3 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6bc5101688190a8b7e41e28b373bc |
completed | May 3, 2026, 3:09 a.m. |
| PD | Predicate disambiguation | batch_69f6b632cf788190a3d0c08cd026b84b |
completed | May 3, 2026, 2:42 a.m. |
Created at: May 1, 2026, 12:41 a.m.