Triple
T33060248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Big Bounce |
E845951
|
entity |
| Predicate | hasAdaptationCountryOfOrigin |
P21186
|
FINISHED |
| Object | United States |
—
|
NE NERFINISHED |
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: United States | Statement: [The Big Bounce, hasAdaptationCountryOfOrigin, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdaptationCountryOfOrigin Context triple: [The Big Bounce, hasAdaptationCountryOfOrigin, United States]
-
A.
nationalityInAdaptation
Indicates that an entity’s nationality, as portrayed in an adaptation, is specified or differs from its original source.
-
B.
televisionAdaptationCountry
Indicates the country in which a television adaptation of a work was produced or primarily created.
-
C.
adaptationCountry
chosen
Indicates the country in which an adaptation (such as a remake, translation, or localized version) of an original work is produced or set.
-
D.
hasAdaptationsIn
Indicates that something possesses or exhibits adaptations within a particular context, environment, or domain.
-
E.
adaptedInLanguage
Indicates that a work or content has been modified or translated so it can be presented or understood in a specified language.
- 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_69f3495333b8819095e9af56855b9061 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fd57ba740c8190bd1d40166fccccb7 |
completed | May 8, 2026, 3:25 a.m. |
| PD | Predicate disambiguation | batch_69fd55ee82b881908a639da3a41b3af6 |
completed | May 8, 2026, 3:18 a.m. |
Created at: May 1, 2026, 1:25 a.m.