Triple
T10404149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | K.Dot |
E245221
|
entity |
| Predicate | occupationOfBearer |
P93726
|
FINISHED |
| Object | rapper |
—
|
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: rapper | Statement: [K.Dot, occupationOfBearer, rapper]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: occupationOfBearer Context triple: [K.Dot, occupationOfBearer, rapper]
-
A.
occupationOf
Indicates that one entity holds or performs the job, role, or profession associated with another entity.
-
B.
occupationOfAssociatedPerson
Indicates the job or professional role held by a person who is associated with another referenced entity.
-
C.
occupationDuringAlias
Indicates that an entity held a particular occupation specifically during the time period when it was known by a given alias.
-
D.
hasNotableBearerOccupation
Indicates that an entity is associated with a notable person who holds a specific occupation.
-
E.
originalHolderOccupation
Indicates the occupation or professional role held by the entity that originally possessed or owned another 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_69d381be340c8190b05998703d42d224 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9e5fb58819081d7d3e1dc625197 |
completed | April 7, 2026, 11:26 a.m. |
| PD | Predicate disambiguation | batch_69d4dfb438c481908dff87c47de2f069 |
completed | April 7, 2026, 10:43 a.m. |
| PDg | Predicate description generation | batch_69d4e944fac4819093b0312aa0efd729 |
completed | April 7, 2026, 11:23 a.m. |
Created at: April 6, 2026, 12:08 p.m.