Triple
T10811562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexander Sebastian |
E255111
|
entity |
| Predicate | homeLocationInFilm |
P47721
|
FINISHED |
| Object | mansion in Rio de Janeiro |
—
|
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: mansion in Rio de Janeiro | Statement: [Alexander Sebastian, homeLocationInFilm, mansion in Rio de Janeiro]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: homeLocationInFilm Context triple: [Alexander Sebastian, homeLocationInFilm, mansion in Rio de Janeiro]
-
A.
residenceAtStartOfFilm
chosen
Indicates the place where a person or character is living at the beginning of the film.
-
B.
filmLocationFor
Indicates a relationship where a specific place serves as the filming location for a particular film or production.
-
C.
formerFilmingLocation
Indicates that a place was once used as a filming location for a work but is no longer used for that purpose.
-
D.
workLocationOfFictionalCharacter
Indicates the place or organization where a fictional character is depicted as working within their narrative context.
-
E.
primaryLocationOfAppearances
Indicates the main place where an entity most frequently appears or is featured.
- 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_69d6aa61c15c8190a1839550c56e75e1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d733b7bfac8190b6ae34144376d6ad |
completed | April 9, 2026, 5:05 a.m. |
| PD | Predicate disambiguation | batch_69d6f3188f00819094ee8d65b187a333 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:18 p.m.