Triple
T18779712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Summerisle |
E459223
|
entity |
| Predicate | filmProductionLocationDouble |
P44217
|
FINISHED |
| Object | various locations in Scotland |
—
|
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: various locations in Scotland | Statement: [Summerisle, filmProductionLocationDouble, various locations in Scotland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmProductionLocationDouble Context triple: [Summerisle, filmProductionLocationDouble, various locations in Scotland]
-
A.
countryOfFilming
Indicates the country where the filming or production of a work physically took place.
-
B.
filmLocationFor
Indicates a relationship where a specific place serves as the filming location for a particular film or production.
-
C.
filmingLocationContext
chosen
Indicates the contextual relationship specifying where the filming of an event, scene, or production took place.
-
D.
numberOfCountriesFilmedIn
Indicates the total count of distinct countries in which the filming of an entity took place.
-
E.
notableFilmingLocation
Indicates that a place served as a significant or well-known location where a film or television production was shot.
- 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_69d8d396f54c8190ba49db31e8743842 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5933e35a481908c21f7f488e1dd99 |
completed | April 20, 2026, 2:45 a.m. |
| PD | Predicate disambiguation | batch_69e48d1126e4819099607837ed5aadca |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:52 a.m.