Triple
T37176715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marie-Blanche Vasnier |
E921069
|
entity |
| Predicate | hasMusicalRelationshipWith |
P130983
|
FINISHED |
| Object | Claude Debussy |
—
|
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: Claude Debussy | Statement: [Marie-Blanche Vasnier, hasMusicalRelationshipWith, Claude Debussy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMusicalRelationshipWith Context triple: [Marie-Blanche Vasnier, hasMusicalRelationshipWith, Claude Debussy]
-
A.
hasMusicalStyleSimilarTo
Indicates that two entities share a comparable or closely related musical style or sound.
-
B.
hasMusicalWorkType
Indicates that a musical work is associated with a specific type or category of musical composition.
-
C.
musicalArtistAssociated
Indicates a relationship where one musical artist is professionally connected or affiliated with another, such as through collaboration, membership, or frequent association.
-
D.
musicalCollaborator
Indicates a relationship where two or more entities work together in creating, performing, or producing music.
-
E.
musicalAssociation
chosen
Indicates a relationship where entities are connected through music, such as collaboration, influence, shared performance, or other musically relevant association.
- 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_69f76ea16f288190b445aa1604d996f4 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fea5e828cc8190a9b755a645dc56d2 |
completed | May 9, 2026, 3:11 a.m. |
| PD | Predicate disambiguation | batch_69fea36443f08190b2aced9b4a0525fd |
completed | May 9, 2026, 3 a.m. |
Created at: May 3, 2026, 4:15 p.m.