Triple
T37388402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kent Nagano |
E928634
|
entity |
| Predicate | hasBeenMusicDirectorOf |
P193228
|
FINISHED |
| Object | Orchestre symphonique de Montréal |
—
|
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: Orchestre symphonique de Montréal | Statement: [Kent Nagano, hasBeenMusicDirectorOf, Orchestre symphonique de Montréal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBeenMusicDirectorOf Context triple: [Kent Nagano, hasBeenMusicDirectorOf, Orchestre symphonique de Montréal]
-
A.
hasMusicDirector
Indicates that an entity (such as a film, show, or production) is associated with a specific person who served as its music director.
-
B.
workedAsDirectorFor
Indicates that one entity held the role of director in relation to another entity, such as an organization, project, or production.
-
C.
directorOfWorkHeAppearsIn
Indicates that a person serves as the director of a work (such as a film, show, or production) in which he himself appears.
-
D.
workOfDirectorKnownFor
Indicates that a work (such as a film or show) is directed by a person for whom this work is one of their notable or best-known creations.
-
E.
hasDirectedFeatureFilm
Indicates that a person has directed a particular feature-length film.
- 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_69f76ebb10c481909b54b9dba263e29f |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fd3a69f1e08190a11aed015bff0858 |
completed | May 8, 2026, 1:20 a.m. |
| PD | Predicate disambiguation | batch_69fd39124180819080ca7911d3515d6d |
completed | May 8, 2026, 1:14 a.m. |
| PDg | Predicate description generation | batch_69fd3a6905b88190ae12b43576f4cc63 |
completed | May 8, 2026, 1:20 a.m. |
Created at: May 3, 2026, 4:16 p.m.