Triple
T6427242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Black Room |
E128089
|
entity |
| Predicate | leadActorRoleCount |
P32517
|
FINISHED |
| Object | dual role |
—
|
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: dual role | Statement: [The Black Room, leadActorRoleCount, dual role]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadActorRoleCount Context triple: [The Black Room, leadActorRoleCount, dual role]
-
A.
featuresActorInMultipleRoles
chosen
Indicates that a work includes an actor who portrays more than one distinct role within that same work.
-
B.
leadActorAlsoDirector
Indicates that the person who plays the lead acting role in a production is also the director of that same production.
-
C.
leadActorEthnicity
Indicates the ethnic background or identity of the primary (lead) actor in a work.
-
D.
starredActor
Indicates that an actor performed a leading or significant role in a particular production or work.
-
E.
oftenPlayedBy
Indicates that one entity frequently performs, portrays, or executes another entity, such as a role, character, or piece of music.
- 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_69c00838de888190af2eec0b80495efa |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c06920cef48190a884df8f12987a0d |
completed | March 22, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69c060f780b08190aa650b4d1fc51f21 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:44 p.m.