Triple
T37632751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shibuya University Network |
E936396
|
entity |
| Predicate | usesUrbanSpaceAsCampus |
P130756
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Shibuya University Network, usesUrbanSpaceAsCampus, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesUrbanSpaceAsCampus Context triple: [Shibuya University Network, usesUrbanSpaceAsCampus, yes]
-
A.
campusUse
Indicates that something is intended for, associated with, or occurring in the use or activities of a campus or campus community.
-
B.
usesCampusAsLaboratory
chosen
Indicates that an entity employs the physical campus environment, operations, or community as a practical setting for experimentation, learning, or research activities.
-
C.
cityCampus
Indicates that a campus is located within or associated with a particular city.
-
D.
campusDesign
Indicates the relationship between an educational institution and the overall planning, layout, and architectural design of its campus environment.
-
E.
campusUsedBy
Indicates that a particular campus is utilized or occupied by a specified group, organization, or set of entities.
- 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_69f76ed24820819081bafd36e9088701 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbaa1321b48190af92a3e7ec24ec5b |
completed | May 6, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69fba8860f98819080b7bab05837b974 |
completed | May 6, 2026, 8:45 p.m. |
Created at: May 3, 2026, 4:18 p.m.