Triple
T29068863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King Daddy |
E735757
|
entity |
| Predicate | hasPerformerNotableRoleInGenre |
P88335
|
FINISHED |
| Object | pioneer of reggaeton |
—
|
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: pioneer of reggaeton | Statement: [King Daddy, hasPerformerNotableRoleInGenre, pioneer of reggaeton]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPerformerNotableRoleInGenre Context triple: [King Daddy, hasPerformerNotableRoleInGenre, pioneer of reggaeton]
-
A.
hasGenreInRoles
Indicates that an entity participates in roles associated with a particular genre or set of genres.
-
B.
hasPerformerCredit
Indicates that a performer is credited for their role or contribution in a specific work, event, or production.
-
C.
isInGenreOfArtistCareer
Indicates that an artist’s career belongs to or is categorized within a particular artistic genre.
-
D.
hasFilmographyType
Indicates the type or category of film-related work associated with an entity (e.g., actor, director, producer) within its filmography.
-
E.
knownForGenre
chosen
Indicates that an entity is recognized or notable for working in, producing, or being associated with a particular genre.
- 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_69f077e9b0a48190bb79548279cb7f64 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f7b0e5744c8190a22c1e1d6fcfa466 |
completed | May 3, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f7ab70d034819080295628497d8582 |
completed | May 3, 2026, 8:09 p.m. |
Created at: April 28, 2026, 10:19 a.m.