Triple
T13056461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kim Burrell |
E327587
|
entity |
| Predicate | occupationSector |
P62538
|
FINISHED |
| Object | Christian music |
—
|
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: Christian music | Statement: [Kim Burrell, occupationSector, Christian music]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: occupationSector Context triple: [Kim Burrell, occupationSector, Christian music]
-
A.
ownerSector
Indicates the sector or industry category to which the owner of an entity belongs.
-
B.
hasOccupationSector
chosen
Indicates that an entity’s occupation belongs to or is categorized within a particular economic or professional sector.
-
C.
occupationType
Indicates the specific kind or category of work, profession, or role that an entity performs or holds.
-
D.
professionalSector
Indicates the industry or field in which an entity conducts its professional or occupational activities.
-
E.
economicSectorDominant
Indicates that one economic sector holds a leading or controlling position relative to others in terms of influence, output, or importance.
- 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_69d8076e64308190904fb5c93517c901 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d98a9829b48190b23624b6b3df4600 |
completed | April 10, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69d9803aca4c8190b1015cd159cc47a9 |
completed | April 10, 2026, 10:56 p.m. |
Created at: April 9, 2026, 8:58 p.m.