Triple
T3833643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don Simpson/Jerry Bruckheimer Films |
E91074
|
entity |
| Predicate | typicalBudgetLevel |
P8208
|
FINISHED |
| Object | big-budget |
—
|
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: big-budget | Statement: [Don Simpson/Jerry Bruckheimer Films, typicalBudgetLevel, big-budget]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalBudgetLevel Context triple: [Don Simpson/Jerry Bruckheimer Films, typicalBudgetLevel, big-budget]
-
A.
budgetLevel
chosen
Indicates the relative amount of financial resources allocated or available for something, typically categorized by level (e.g., low, medium, high).
-
B.
budgetFrom
Indicates that a budget or funding allocation originates from or is provided by a particular source.
-
C.
budgetType
Indicates the classification or category of a budget associated with an entity or financial activity.
-
D.
usesSalaryBudgets
Indicates that one entity allocates or manages financial resources for compensation based on predefined salary budgets associated with another entity.
-
E.
typicalGradeLevel
Indicates the usual or most common educational grade level at which something (such as a concept, resource, or skill) is intended to be taught or is typically encountered.
- 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_69aed960b538819096561c8ed448dec9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeeb88b8a8819082d4bdbc5bc45366 |
completed | March 9, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69aee74c2e04819094b94b3c0bac1806 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:17 p.m.