Triple
T27202544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nella Fantasia |
E683771
|
entity |
| Predicate | derivesFromFilmScoreOf |
P57302
|
FINISHED |
| Object | The Mission |
—
|
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: The Mission | Statement: [Nella Fantasia, derivesFromFilmScoreOf, The Mission]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: derivesFromFilmScoreOf Context triple: [Nella Fantasia, derivesFromFilmScoreOf, The Mission]
-
A.
hasFilmScoreBy
Indicates that a film’s musical score was composed or created by a specified person or entity.
-
B.
hasFilmScore
chosen
Indicates that one entity serves as the musical score or soundtrack composed for a particular film.
-
C.
isSoundtrackOf
Indicates that a piece of music or collection of music serves as the soundtrack for a particular work, such as a film, game, or show.
-
D.
scoredBySameComposerAsFilm
Indicates that the work is scored by a composer who also composed the score for the referenced film.
-
E.
hasFilmScoreStyle
Indicates a relationship where a film is associated with a particular style or type of musical score used in it.
- 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_69eefad1fd5c8190a4a46ea6afe58bfa |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f65f7731e4819099d5bd3d915ee266 |
completed | May 2, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f65c1f94ac8190bc6fbc7916fc0d82 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 27, 2026, 9:36 a.m.