Triple
T32546137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chuo University Football Club |
E831851
|
entity |
| Predicate | feederRelationshipTo |
P47841
|
FINISHED |
| Object | Avispa Fukuoka |
—
|
NE NERFINISHED |
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: Avispa Fukuoka | Statement: [Chuo University Football Club, feederRelationshipTo, Avispa Fukuoka]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: feederRelationshipTo Context triple: [Chuo University Football Club, feederRelationshipTo, Avispa Fukuoka]
-
A.
hasFeederRelationshipTo
Indicates that one entity serves as a source of nourishment, resources, or input that sustains, supports, or feeds another entity.
-
B.
feederTeamRelationship
chosen
Indicates a developmental or subordinate team relationship where one team serves as a source of talent or resources for another, typically higher-level, team.
-
C.
inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
-
D.
relationshipTarget
Indicates that an entity is the object or recipient toward which a specified relationship is directed.
-
E.
fareRelationship
Indicates a relationship between entities based on the cost, pricing, or fare charged for a service or trip.
- 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_69f34925fd08819084cfe4ec566cb704 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c5bfe55881909a20ef79180d19c4 |
completed | May 3, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2a14b081908162923dfbf0a6f4 |
completed | May 3, 2026, 3:12 a.m. |
Created at: May 1, 2026, 1:02 a.m.