Triple
T30347777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shuchiin Academy |
E771910
|
entity |
| Predicate | hasStudentCouncilVicePresident |
P196657
|
FINISHED |
| Object | Kaguya Shinomiya |
—
|
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: Kaguya Shinomiya | Statement: [Shuchiin Academy, hasStudentCouncilVicePresident, Kaguya Shinomiya]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStudentCouncilVicePresident Context triple: [Shuchiin Academy, hasStudentCouncilVicePresident, Kaguya Shinomiya]
-
A.
hasViceChair
Indicates that an entity holds the role or position of vice chair in relation to another entity (such as an organization, committee, or group).
-
B.
hasElectedViceMayor
Indicates that an entity has a person who holds the position of elected vice mayor for it.
-
C.
hasViceMayor
Indicates that an entity holds the position of vice mayor for a given administrative or governmental body.
-
D.
hasViceChairTitle
Indicates that an entity holds the position or bears the formal title of vice chair in relation to another entity or organization.
-
E.
hasViceChancellor
Indicates that one entity serves as the vice chancellor of 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_69f2248b9a208190bc3e6804acd5afd6 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fe610e1f6881908f10070ba64643cf |
completed | May 8, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69fe604c6c008190ad659e9b9fa82f7b |
completed | May 8, 2026, 10:14 p.m. |
| PDg | Predicate description generation | batch_69fe610d75a48190bfd08a9bb957fcd3 |
completed | May 8, 2026, 10:17 p.m. |
Created at: April 29, 2026, 7:56 p.m.