Triple
T26380694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Makeda Marley |
E663115
|
entity |
| Predicate | genreAssociatedViaFamily |
P165036
|
FINISHED |
| Object | reggae |
—
|
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: reggae | Statement: [Makeda Marley, genreAssociatedViaFamily, reggae]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreAssociatedViaFamily Context triple: [Makeda Marley, genreAssociatedViaFamily, reggae]
-
A.
genreAssociatedWith
Indicates a relationship where a work, item, or entity is linked to or categorized under a particular genre.
-
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.
genreOfAssociatedPerson
Indicates that a particular genre is associated with a given person, such as an artist, author, or performer.
-
D.
genreAssociatedWithSpouse
Indicates that a particular genre is associated with, or characterizes, the spouse of the referenced entity.
-
E.
hasPerformerFamily
Indicates that an entity has a family member who performs or participates as a performer in relation to that entity.
- 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_69ee88374adc81909868f3bab374a32f |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f65705a3048190a3728b695ba2ae65 |
completed | May 2, 2026, 7:56 p.m. |
| PD | Predicate disambiguation | batch_69f651a731508190bb0c8c2462eba224 |
completed | May 2, 2026, 7:33 p.m. |
| PDg | Predicate description generation | batch_69f6562ef4e4819082ce6abd41b74dc5 |
completed | May 2, 2026, 7:53 p.m. |
Created at: April 26, 2026, 11:17 p.m.