Triple
T2198810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nope |
E50439
|
entity |
| Predicate | productionBudget |
P36902
|
FINISHED |
| Object | approximately $68 million |
—
|
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: approximately $68 million | Statement: [Nope, productionBudget, approximately $68 million]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: productionBudget Context triple: [Nope, productionBudget, approximately $68 million]
-
A.
productionValue
Indicates the quantitative amount or worth of output generated in a production process or activity.
-
B.
boxOfficeGrossUSD
Indicates the total amount of money an entity earned at the box office, expressed in U.S. dollars.
-
C.
budget
Indicates that an entity allocates, plans, or assigns specific financial resources for another entity, activity, or time period.
-
D.
budgetFrom
Indicates that a budget or funding allocation originates from or is provided by a particular source.
-
E.
hasBoxOffice
Indicates that an entity (typically a film or performance) has a specific box office revenue amount or record associated with it.
- F. None of above. chosen
Provenance (4 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_69a88b044ab48190add007487680f009 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abbf7b65cc8190bcc5a5c52b90f33b |
completed | March 7, 2026, 6:02 a.m. |
| PD | Predicate disambiguation | batch_69abbda706f4819094de73e1d1d1f539 |
completed | March 7, 2026, 5:54 a.m. |
| PDg | Predicate description generation | batch_69abbf35c994819088a093c412931de4 |
completed | March 7, 2026, 6:01 a.m. |
Created at: March 4, 2026, 7:46 p.m.