Triple
T2789409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ronald Colman |
E61891
|
entity |
| Predicate | screenPersona |
P32702
|
FINISHED |
| Object | suave |
—
|
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: suave | Statement: [Ronald Colman, screenPersona, suave]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: screenPersona Context triple: [Ronald Colman, screenPersona, suave]
-
A.
characterDescription
chosen
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.
characterRoleSwap
Indicates a relationship where two characters exchange or assume each other’s narrative roles or functions within a story or scenario.
-
D.
aiCharacter
Indicates that an entity is a character or agent whose behavior or role is driven by artificial intelligence.
-
E.
character2
Indicates that a second character entity is involved in the relationship or context defined by the predicate.
- 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_69ab4b7f51d881908768300ebd2fbdae |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdeea881481908d759c72798a50fb |
completed | March 7, 2026, 8:16 a.m. |
| PD | Predicate disambiguation | batch_69abdd025c948190a97dd961a9592bac |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:58 p.m.