Triple
T37666649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kintango |
E937833
|
entity |
| Predicate | portrayedInCountryOfProduction |
P110306
|
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: [Kintango, portrayedInCountryOfProduction, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayedInCountryOfProduction Context triple: [Kintango, portrayedInCountryOfProduction, United States]
-
A.
portrayedByCountryOfOrigin
Indicates that an entity is depicted or represented by something originating from a specified country.
-
B.
productionCountryOfWorkAppearsIn
chosen
Indicates that a country is the production country of a work in which a given entity appears.
-
C.
modeledInCountry
Indicates that something (such as a model, design, or representation) was created, developed, or constructed within the specified country.
-
D.
productionCountries
Indicates the countries where a work (such as a film or TV show) was produced or financed.
-
E.
isProducedIn
Indicates that something is created, manufactured, or generated within a particular place, context, or process.
- 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_69f76ed6df7c8190b018e5baea716ceb |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ffada24d188190a576a02dc280a7fb |
completed | May 9, 2026, 9:56 p.m. |
| PD | Predicate disambiguation | batch_69ffad46d6ac819081772f408b1389d5 |
completed | May 9, 2026, 9:55 p.m. |
Created at: May 3, 2026, 4:18 p.m.