Triple
T31675233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kingdom |
E808380
|
entity |
| Predicate | characterAlveyKulinaOccupation |
P197360
|
FINISHED |
| Object | MMA gym owner |
—
|
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: MMA gym owner | Statement: [Kingdom, characterAlveyKulinaOccupation, MMA gym owner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterAlveyKulinaOccupation Context triple: [Kingdom, characterAlveyKulinaOccupation, MMA gym owner]
-
A.
knownForRoleIn
Indicates that an entity is recognized or notable for performing a particular role in a specific work, project, or context.
-
B.
VueltabajoKnownFor
Indicates that Vueltabajo is widely recognized or notable for a particular characteristic, product, or feature.
-
C.
playwrightKnownFor
Indicates that a playwright is especially recognized or notable for a particular work, style, or contribution.
-
D.
creatorKnownFor
Indicates that a creator is especially recognized or notable for a particular work, contribution, or achievement.
-
E.
featuresProtagonistOccupation
Indicates that the work’s main character has a specified occupation or job role.
- 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_69fe8ddf70e48190a917eb9e8f7b6966 |
completed | May 9, 2026, 1:29 a.m. |
| PD | Predicate disambiguation | batch_69fe87ef94dc81909bb00ec8d6de9bcd |
completed | May 9, 2026, 1:03 a.m. |
| PDg | Predicate description generation | batch_69fe8dde8d008190b03dc0f97618073c |
completed | May 9, 2026, 1:29 a.m. |
Created at: April 30, 2026, 11:02 p.m.