Triple
T34991005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vladimir Sokoloff |
E1009382
|
entity |
| Predicate | portrayedRolesOften |
P104626
|
FINISHED |
| Object | wise characters |
—
|
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: wise characters | Statement: [Vladimir Sokoloff, portrayedRolesOften, wise characters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayedRolesOften Context triple: [Vladimir Sokoloff, portrayedRolesOften, wise characters]
-
A.
hasPortrayedRole
chosen
Indicates that an entity has performed or depicted a specific role or character, typically in a work such as a film, play, or television show.
-
B.
hasPortrayedPersonRole
Indicates that an entity has performed or held a specific role in portraying a particular person (e.g., in a film, play, or other representation).
-
C.
portrayedByAlsoPlays
Indicates that the actor who portrays a given character also plays another specified role or character.
-
D.
alsoPortrayedBy
Indicates that the same role or character is portrayed by an additional, different performer or actor.
-
E.
featuresActorInMultipleRoles
Indicates that a work includes an actor who portrays more than one distinct role within that same work.
- 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_69f76dca50dc8190b71f39defe186be8 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff29d831b881908d485609e0fc1d0b |
completed | May 9, 2026, 12:34 p.m. |
| PD | Predicate disambiguation | batch_69ff28f9f9e4819087f3402735de66c7 |
completed | May 9, 2026, 12:30 p.m. |
Created at: May 3, 2026, 4:01 p.m.