Triple
T21105074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chris Keller |
E520016
|
entity |
| Predicate | relationshipToMusic |
P33013
|
FINISHED |
| Object | professional musician |
—
|
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: professional musician | Statement: [Chris Keller, relationshipToMusic, professional musician]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToMusic Context triple: [Chris Keller, relationshipToMusic, professional musician]
-
A.
influencesMusicOf
Indicates that one entity has an effect on, shapes, or contributes to the musical style, content, or development of another entity.
-
B.
genreRelation
Indicates a relationship where one entity is categorized as having, belonging to, or being associated with a particular genre defined by another entity.
-
C.
associatedMusic
Indicates a relationship where one entity is linked to or connected with a piece of music, such as being used by, related to, or thematically tied to that music.
-
D.
favoriteMusician
Indicates that one entity is the musician whom another entity prefers above all others.
-
E.
subjectRelationToArtist
chosen
Indicates the nature of the relationship or connection that the subject has to the artist.
- 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_69e0b508d8dc81909be940dafe36c8f7 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e71b6150f08190a3738f1eda7fa834 |
completed | April 21, 2026, 6:38 a.m. |
| PD | Predicate disambiguation | batch_69e5dbff56848190a03b350a9305c612 |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 16, 2026, 2:53 p.m.