Triple
T17412133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Preacher's Wife (film score) |
E423391
|
entity |
| Predicate | containsMusicalStyle |
P22764
|
FINISHED |
| Object | rich choral arrangements |
—
|
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: rich choral arrangements | Statement: [The Preacher's Wife (film score), containsMusicalStyle, rich choral arrangements]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsMusicalStyle Context triple: [The Preacher's Wife (film score), containsMusicalStyle, rich choral arrangements]
-
A.
includesMusicalStyle
chosen
Indicates that one entity encompasses, features, or incorporates a particular musical style as part of its content or character.
-
B.
hasMusicalStyleCharacteristic
Indicates that something possesses or exhibits a particular musical style as a defining characteristic.
-
C.
hasSongStyle
Indicates that an entity possesses, is characterized by, or is associated with a particular style or genre of song.
-
D.
styleOfMusic
Indicates the musical genre or stylistic category that characterizes a piece of music, artist, or performance.
-
E.
hasMusicalStyleSimilarTo
Indicates that two entities share a comparable or closely related musical style or sound.
- 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_69d889d7d27c819088486ce3f0627fa1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43b0b56788190ba012788f32afb78 |
completed | April 19, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69e3b02e6cc88190986e85e64ce9383e |
completed | April 18, 2026, 4:24 p.m. |
Created at: April 10, 2026, 5:46 a.m.