Triple
T2628886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Debi Mazar |
E59186
|
entity |
| Predicate | televisionSeriesRole |
P1668
|
FINISHED |
| Object | Shauna Roberts in Entourage |
—
|
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: Shauna Roberts in Entourage | Statement: [Debi Mazar, televisionSeriesRole, Shauna Roberts in Entourage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: televisionSeriesRole Context triple: [Debi Mazar, televisionSeriesRole, Shauna Roberts in Entourage]
-
A.
playedRoleIn
chosen
Indicates that an entity performed or assumed a specific role or character within a particular event, production, or context.
-
B.
actingRoleType
Indicates the specific type or category of role an entity performs when acting in a particular capacity or function.
-
C.
hasFictionalRole
Indicates that an entity plays or is assigned a specific role within a fictional work or narrative.
-
D.
roleInScene
Indicates that an entity participates in a particular scene with a specific role or function within that scene.
-
E.
playedBy
Indicates that a role, character, or performance is portrayed or executed by a specific person or agent.
- 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_69ab4ac558388190962492cd2e1b0ce6 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abdb0e7b888190bfa5d2e33f00ec0f |
completed | March 7, 2026, 8 a.m. |
| PD | Predicate disambiguation | batch_69abd810d7f481908e81c305772c4c14 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:50 p.m.