Triple
T25861978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Werewolf (1996 film) |
E651502
|
entity |
| Predicate | hasProductionBudget |
P36902
|
FINISHED |
| Object | low 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: low budget | Statement: [Werewolf (1996 film), hasProductionBudget, low budget]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProductionBudget Context triple: [Werewolf (1996 film), hasProductionBudget, low budget]
-
A.
productionBudget
chosen
Indicates the amount of money allocated or spent to produce a work, such as a film, show, or similar production.
-
B.
productionValue
Indicates the quantitative amount or worth of output generated in a production process or activity.
-
C.
hasBoxOffice
Indicates that an entity (typically a film or performance) has a specific box office revenue amount or record associated with it.
-
D.
boxOfficeGrossUSD
Indicates the total amount of money an entity earned at the box office, expressed in U.S. dollars.
-
E.
hasBoxOfficeType
Indicates the classification of a work’s box office performance or revenue category (e.g., type or scale of its box office results).
- 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_69e7ab3a199c81909227cb964cacfe24 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f7675b12848190a3569cfda29c5b0e |
completed | May 3, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69f762f4b59481909f70074f11825bfb |
completed | May 3, 2026, 3 p.m. |
Created at: April 22, 2026, 8:05 a.m.