Triple
T19321486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kathy Sledge |
E483234
|
entity |
| Predicate | hasGenreWithGroup |
P124610
|
FINISHED |
| Object | R&B with Sister Sledge |
—
|
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: R&B with Sister Sledge | Statement: [Kathy Sledge, hasGenreWithGroup, R&B with Sister Sledge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenreWithGroup Context triple: [Kathy Sledge, hasGenreWithGroup, R&B with Sister Sledge]
-
A.
hasGenreRelation
chosen
Indicates that there is an association between an entity and a specific genre, specifying the type or category it belongs to.
-
B.
hasGenreInRoles
Indicates that an entity participates in roles associated with a particular genre or set of genres.
-
C.
hasGenreScope
Indicates that something (such as a work, collection, or classification) is limited to, defined by, or applicable within a particular genre or set of genres.
-
D.
hasUseGenre
Indicates that something (such as a work, product, or item) is associated with or categorized under a particular genre for its use or purpose.
-
E.
hasGenreFeature
Indicates that something possesses a characteristic, element, or trait 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_69d8e8d13e3c81909d91d1d5ec37c095 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e60d88951081909f7ce6e0610c7258 |
completed | April 20, 2026, 11:27 a.m. |
| PD | Predicate disambiguation | batch_69e4dd0ef66881909d489d634eee817a |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:32 p.m.