Triple
T12893276
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Moscow as young Josh Baskin |
E308421
|
entity |
| Predicate | portrayalContinuity |
P107301
|
FINISHED |
| Object | sameCharacterDifferentAge |
—
|
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: sameCharacterDifferentAge | Statement: [David Moscow as young Josh Baskin, portrayalContinuity, sameCharacterDifferentAge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayalContinuity Context triple: [David Moscow as young Josh Baskin, portrayalContinuity, sameCharacterDifferentAge]
-
A.
portrayalFeature
Indicates that one entity serves as a characteristic, aspect, or attribute highlighted in the depiction or representation of another entity.
-
B.
cultContinuity
Indicates the continuation or persistence of a religious cult’s practices, beliefs, or traditions over time.
-
C.
portrayalRecognition
Indicates that one entity recognizes or identifies another entity as a portrayal or representation of a particular subject or character.
-
D.
portrayalStart
Indicates the point in time or sequence at which a particular portrayal or depiction of something begins.
-
E.
portrayalFormat
Indicates the medium or format in which something is portrayed or represented (e.g., painting, sculpture, film, digital).
- F. None of above. chosen
Provenance (4 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_69d7bdf7c1f0819098102569a8d8cbf5 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971484aa08190a8adfafabe600903 |
completed | April 10, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69d96fa776648190b9b5c30722ea50b6 |
completed | April 10, 2026, 9:46 p.m. |
| PDg | Predicate description generation | batch_69d9713e45a88190acd346f066093550 |
completed | April 10, 2026, 9:53 p.m. |
Created at: April 9, 2026, 5:40 p.m.