Triple
T35709272
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Théâtre Optique |
E1031807
|
entity |
| Predicate | soundAccompaniment |
P184079
|
FINISHED |
| Object | live music |
—
|
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: live music | Statement: [Théâtre Optique, soundAccompaniment, live music]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: soundAccompaniment Context triple: [Théâtre Optique, soundAccompaniment, live music]
-
A.
vocalAccompaniment
Indicates that one entity provides vocal support or accompaniment to another entity’s primary performance or action.
-
B.
hasPianoAccompaniment
Indicates that something (such as a musical work or performance) is accompanied by a piano part.
-
C.
soundMotif
Indicates a recurring or thematically significant sound pattern associated with an entity, event, or context.
-
D.
accompanimentType
Indicates the specific manner or style in which one entity accompanies or supports another (e.g., musically, contextually, or functionally).
-
E.
musicElement
Indicates a relationship where something functions as a component or structural unit within a piece of music or musical composition.
- F. None of above. chosen
Provenance (4 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_69f76e0df1d08190965b1c6dff94c391 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7aaabb58c8190bf81673608ecfb6e |
completed | May 3, 2026, 8:06 p.m. |
| PD | Predicate disambiguation | batch_69f7a8d219f8819081dc4ce3c83ca0cb |
completed | May 3, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69f7aa6795f481908940838ee7041ff5 |
completed | May 3, 2026, 8:04 p.m. |
Created at: May 3, 2026, 4:05 p.m.