Triple
T22390681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King of Latin Pop |
E553502
|
entity |
| Predicate | appliedToArtistKnownFor |
P86546
|
FINISHED |
| Object | bilingual Spanish-English repertoire |
—
|
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: bilingual Spanish-English repertoire | Statement: [King of Latin Pop, appliedToArtistKnownFor, bilingual Spanish-English repertoire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliedToArtistKnownFor Context triple: [King of Latin Pop, appliedToArtistKnownFor, bilingual Spanish-English repertoire]
-
A.
appliesToArtist
chosen
Indicates that something (such as a rule, condition, attribute, or action) is relevant or applicable specifically to an artist.
-
B.
referencedByArtist
Indicates that an artist has mentioned, cited, or otherwise referred to the target entity in their work or related materials.
-
C.
hasArtist
Indicates that an entity (such as a work or item) is associated with or created by a specific artist.
-
D.
hasArtistRole
Indicates that an entity serves in the capacity or role of an artist in relation to another entity or context.
-
E.
mentionsArtist
Indicates that one entity explicitly refers to or cites an artist in its content or context.
- 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_69e11e4cf87c8190a1ff474daec326b7 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15859853c8190b849cb34a94106da |
completed | April 29, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69e73015484c8190a9a0b9f554b61a81 |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:45 p.m.