Triple
T1152115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aoyama Gakuin University |
E23697
|
entity |
| Predicate | cityCampusCharacteristic |
P13638
|
FINISHED |
| Object | located near Omotesando and Shibuya areas |
—
|
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: located near Omotesando and Shibuya areas | Statement: [Aoyama Gakuin University, cityCampusCharacteristic, located near Omotesando and Shibuya areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityCampusCharacteristic Context triple: [Aoyama Gakuin University, cityCampusCharacteristic, located near Omotesando and Shibuya areas]
-
A.
cityCampus
Indicates that a campus is located within or associated with a particular city.
-
B.
campusLandmark
Indicates that something serves as a notable or recognizable landmark located on or associated with a campus.
-
C.
campusType
Indicates the classification or category of a campus based on its type (e.g., main, satellite, urban, rural).
-
D.
hasCampusFeature
Indicates that a campus possesses or includes a specific physical or functional feature.
-
E.
campusDescription
chosen
Indicates a descriptive relationship that specifies details or characteristics of a campus.
- 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_69a493f0d32c8190ac74bad3c87f2641 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bc8d2dd8819081c779d408c2651d |
completed | March 1, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69a4bb50d19c81908a98dbbb04a8906f |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:44 p.m.