Triple
T10607373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dustin Hoffman as Harold Meyerowitz |
E275909
|
entity |
| Predicate | characterAgeDescriptor |
P94896
|
FINISHED |
| Object | aging |
—
|
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: aging | Statement: [Dustin Hoffman as Harold Meyerowitz, characterAgeDescriptor, aging]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterAgeDescriptor Context triple: [Dustin Hoffman as Harold Meyerowitz, characterAgeDescriptor, aging]
-
A.
characterDescription
Indicates that one entity provides a textual description or portrayal of the characteristics, traits, or attributes of another entity.
-
B.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
-
C.
protagonistAge
Indicates the age of the main character or central figure in a narrative or scenario.
-
D.
childCharacter
Indicates that one entity is a child version or child role of another character entity.
-
E.
characterSetting
Indicates that a character is associated with, appears in, or is situated within a particular setting or environment.
- 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_69d6aaf948d88190806cc3a8c47a3fb2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d6df4c38c881908f69bb757b8e03f5 |
completed | April 8, 2026, 11:05 p.m. |
| PD | Predicate disambiguation | batch_69d6dd72c1288190adbb5e79e94c044a |
completed | April 8, 2026, 10:57 p.m. |
| PDg | Predicate description generation | batch_69d6df463ea8819091d6683e476b4f21 |
completed | April 8, 2026, 11:05 p.m. |
Created at: April 8, 2026, 7:32 p.m.