Triple
T28655642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krzysztof Komeda |
E725322
|
entity |
| Predicate | wroteMusicForFilm |
P113320
|
FINISHED |
| Object | "Rosemary’s Baby" |
—
|
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: "Rosemary’s Baby" | Statement: [Krzysztof Komeda, wroteMusicForFilm, "Rosemary’s Baby"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wroteMusicForFilm Context triple: [Krzysztof Komeda, wroteMusicForFilm, "Rosemary’s Baby"]
-
A.
composerOfSoundtrackFor
chosen
Indicates that one entity created the musical score or soundtrack specifically for a work associated with another entity.
-
B.
composedForMusicBy
Indicates that a musical work was specifically created or written by a particular composer.
-
C.
notableSongWrittenFor
Indicates that a particular song was specifically written for a given person, group, work, event, or purpose.
-
D.
scoredBySameComposerAsFilm
Indicates that the work is scored by a composer who also composed the score for the referenced film.
-
E.
hasMusicFilm
Indicates a relationship where a subject is associated with or linked to a film that features or centers around music.
- 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_69f01d84f5f0819087ab5e6143b14ed7 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f65a6c900881908f18b61273d7bf8d |
completed | May 2, 2026, 8:11 p.m. |
| PD | Predicate disambiguation | batch_69f659ce58408190ba9e007b4810d4d0 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 4:55 a.m.