Triple
T11309926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 摂南大学 |
E267809
|
entity |
| Predicate | 教育機関の種別 |
P303
|
FINISHED |
| Object | 高等教育機関 |
—
|
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: 高等教育機関 | Statement: [摂南大学, 教育機関の種別, 高等教育機関]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 教育機関の種別 Context triple: [摂南大学, 教育機関の種別, 高等教育機関]
-
A.
typeOfInstitution
chosen
Indicates the specific kind or category of institution that an entity belongs to or is classified as.
-
B.
educationType
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
-
C.
typeOfUniversity
Indicates the specific category or classification of a university (e.g., public, private, technical, etc.) that an institution belongs to.
-
D.
schoolSector
Indicates the educational sector or category (such as public, private, or charter) to which a school belongs.
-
E.
schoolSystemType
Indicates the classification or organizational model of a school system (e.g., public, private, charter, or other structural type).
- 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9c0b3b88190ac0e3d6a5ad3b9bc |
completed | April 9, 2026, 6:02 p.m. |
| PD | Predicate disambiguation | batch_69d787aa31888190860eecaa80da5b20 |
completed | April 9, 2026, 11:04 a.m. |
Created at: April 8, 2026, 9:32 p.m.