Triple
T31675235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kingdom |
E808380
|
entity |
| Predicate | characterNateKulinaOccupation |
P197394
|
FINISHED |
| Object | professional MMA fighter |
—
|
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: professional MMA fighter | Statement: [Kingdom, characterNateKulinaOccupation, professional MMA fighter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterNateKulinaOccupation Context triple: [Kingdom, characterNateKulinaOccupation, professional MMA fighter]
-
A.
characterAlveyKulinaOccupation
Indicates that the specified occupation is the job or professional role held by the character Alvey Kulina.
-
B.
namedPersonOccupation
Indicates that a person is explicitly identified as having a particular occupation or job role.
-
C.
knownForRoleIn
Indicates that an entity is recognized or notable for performing a particular role in a specific work, project, or context.
-
D.
contestantOccupationDescribedAs
Indicates that a contestant’s occupation is characterized or labeled in a particular way, often as it is described or presented (e.g., in media, documentation, or dialogue).
-
E.
namesakeOccupation
Indicates that one entity’s occupation is the same as, or derived from, the occupation associated with the other entity’s namesake.
- 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_69f348dcf5d48190ac25b1365ae717a8 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fe8f74748c8190bd14a856c057f9f7 |
completed | May 9, 2026, 1:35 a.m. |
| PD | Predicate disambiguation | batch_69fe8e7ed8088190929e0df67aca4de9 |
completed | May 9, 2026, 1:31 a.m. |
| PDg | Predicate description generation | batch_69fe8f730bb88190975bffd49f5e0f3b |
completed | May 9, 2026, 1:35 a.m. |
Created at: April 30, 2026, 11:02 p.m.