Triple
T5709683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sister Mister |
E125872
|
entity |
| Predicate | partOfCastType |
P56852
|
FINISHED |
| Object | ensemble character |
—
|
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: ensemble character | Statement: [Sister Mister, partOfCastType, ensemble character]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfCastType Context triple: [Sister Mister, partOfCastType, ensemble character]
-
A.
featuresCastType
chosen
Indicates that one entity includes or highlights a particular type or category of cast (e.g., actors or performers) associated with it.
-
B.
typicalCasting
Indicates that one entity is the usual or standard casting choice for portraying another entity (such as a role, character, or type).
-
C.
cast
Indicates that an agent selects and assigns a person or thing to play a specific role or function in a production or context.
-
D.
actingRoleType
Indicates the specific type or category of role an entity performs when acting in a particular capacity or function.
-
E.
featuresCastFrom
Indicates that a work (such as a film or show) includes a cast member who originates from a specified source or production.
- 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_69c0082d6fe48190b777fb383769e5c8 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0248c3dac8190824fca9ddde89665 |
completed | March 22, 2026, 5:19 p.m. |
| PD | Predicate disambiguation | batch_69c021c2d8bc8190b947c7d1f423d2f3 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:46 p.m.