Triple
T26592581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Americano (2005 film) |
E667399
|
entity |
| Predicate | hasCountryOfFilming |
P21831
|
FINISHED |
| Object | Spain |
—
|
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: Spain | Statement: [Americano (2005 film), hasCountryOfFilming, Spain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCountryOfFilming Context triple: [Americano (2005 film), hasCountryOfFilming, Spain]
-
A.
countryOfFilming
chosen
Indicates the country where the filming or production of a work physically took place.
-
B.
filmingCountry
Indicates the country where the filming or primary production of a work took place.
-
C.
primaryFilmingRegions
Indicates the main geographic areas where the filming or production of a work primarily took place.
-
D.
numberOfCountriesFilmedIn
Indicates the total count of distinct countries in which the filming of an entity took place.
-
E.
filmingRegions
Indicates the geographic areas or locations where the filming or production of a work takes place.
- 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_69ee9cfc385081909ac9ae178030a06e |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69fdf5d05cc481909ec9e1b1f0784279 |
completed | May 8, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69fdf0cdd6948190838864ab3120dfa6 |
completed | May 8, 2026, 2:18 p.m. |
Created at: April 27, 2026, 2:08 a.m.