Triple
T37409675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jun-fan |
E929526
|
entity |
| Predicate | hasBearerInfluenceOn |
P63153
|
FINISHED |
| Object | mixed martial arts |
—
|
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: mixed martial arts | Statement: [Jun-fan, hasBearerInfluenceOn, mixed martial arts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBearerInfluenceOn Context triple: [Jun-fan, hasBearerInfluenceOn, mixed martial arts]
-
A.
isUnderInfluenceOf
Indicates that one entity is affected, controlled, or significantly shaped by the power, authority, or effect of another entity.
-
B.
hasInfluenceScope
Indicates the range or extent within which an entity’s influence, impact, or authority is effective or applicable.
-
C.
hasAdditionalInfluence
Indicates that one entity exerts extra or supplementary influence on another entity beyond any primary or baseline effect.
-
D.
hasSignificantInfluenceIn
chosen
Indicates that one entity exerts a substantial impact or shaping effect on another entity within a particular domain, context, or outcome.
-
E.
hasRegionalInfluenceFrom
Indicates that one entity’s influence, impact, or authority in a region is derived from or shaped by another entity.
- 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_69f76ebde49481908566cd96b37ccc84 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fd49f6dbac81909744373a357b7982 |
completed | May 8, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69fd48ed68f481908374183c66a6b055 |
completed | May 8, 2026, 2:22 a.m. |
Created at: May 3, 2026, 4:16 p.m.