Triple
T6634537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Human |
E150413
|
entity |
| Predicate | numberOfCountriesFilmedIn |
P71859
|
FINISHED |
| Object | over 60 |
—
|
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: over 60 | Statement: [Human, numberOfCountriesFilmedIn, over 60]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCountriesFilmedIn Context triple: [Human, numberOfCountriesFilmedIn, over 60]
-
A.
countryOfFilming
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.
hasInternationalProductionsIn
Indicates that an entity has produced or staged international versions of its work in the specified location or country.
-
D.
coProductionRegions
Indicates the regions or countries that jointly participated in producing a work (e.g., a film or TV show) as co-producers.
-
E.
nationalCinema
Indicates that a film or cinematic work is associated with, produced by, or representative of a particular nation’s cinema.
- 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_69c687f0ceb08190bf40807bfc605fa5 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6c308a08881908501c862b3029321 |
completed | March 27, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69c6ad024860819084b9b535b136ede6 |
completed | March 27, 2026, 4:14 p.m. |
| PDg | Predicate description generation | batch_69c6c30733908190980f7ffaa5c5527b |
completed | March 27, 2026, 5:48 p.m. |
Created at: March 27, 2026, 1:59 p.m.