Triple
T29231494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Page Marlowe |
E741080
|
entity |
| Predicate | usesCastingConcept |
P133007
|
FINISHED |
| Object | multi-actor single role casting |
—
|
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: multi-actor single role casting | Statement: [Mary Page Marlowe, usesCastingConcept, multi-actor single role casting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesCastingConcept Context triple: [Mary Page Marlowe, usesCastingConcept, multi-actor single role casting]
-
A.
usesCastingOf
Indicates that one entity employs or applies a particular casting of another entity (such as a type, role, or form) in its operation or context.
-
B.
hasCasting
Indicates that an entity features a particular actor or set of actors in its cast.
-
C.
isCastingCategoryFor
Indicates that one entity serves as the casting category or type classification used to group or select another entity in a casting context.
-
D.
hasConceptualUse
chosen
Indicates that one entity is used or applied in a conceptual, abstract, or theoretical way by another entity.
-
E.
castingType
Indicates the specific method or category of casting used to transform or represent one entity in terms of another.
- 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_69f07cbb12bc81908c1971d9de9a8d2a |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f7626667f48190ad90867eb67ec582 |
completed | May 3, 2026, 2:57 p.m. |
| PD | Predicate disambiguation | batch_69f76175d6608190b60b268e20f49ed9 |
completed | May 3, 2026, 2:53 p.m. |
Created at: April 28, 2026, 12:19 p.m.