Triple
T28150897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucky Seven Records |
E714616
|
entity |
| Predicate | hasNotableGenreAssociationWith |
P28041
|
FINISHED |
| Object | British ska |
—
|
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: British ska | Statement: [Lucky Seven Records, hasNotableGenreAssociationWith, British ska]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableGenreAssociationWith Context triple: [Lucky Seven Records, hasNotableGenreAssociationWith, British ska]
-
A.
hasNotableGenre
chosen
Indicates that an entity is significantly associated with a particular genre, such that the genre is especially characteristic or noteworthy for that entity.
-
B.
hasNotableSubgenre
Indicates that one genre is recognized as a particularly significant or prominent subgenre of another genre.
-
C.
hasNotableGenreContext
Indicates that an entity’s genre is significant or noteworthy in understanding its context, interpretation, or impact.
-
D.
hasNotableVersionGenre
Indicates that an entity has a specific version or edition that is associated with a notable genre.
-
E.
hasGenreRelation
Indicates that there is an association between an entity and a specific genre, specifying the type or category it belongs to.
- 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_69efd6b033208190bf74f80a147e2092 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69feff70fbec8190b1ff5f943f29613e |
completed | May 9, 2026, 9:33 a.m. |
| PD | Predicate disambiguation | batch_69fefbcd5b7881909cfe52b32f8a4301 |
completed | May 9, 2026, 9:18 a.m. |
Created at: April 27, 2026, 9:59 p.m.