Triple
T23368288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Yaoundé II |
E593384
|
entity |
| Predicate | primaryCampusSetting |
P49160
|
FINISHED |
| Object | suburban |
—
|
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: suburban | Statement: [University of Yaoundé II, primaryCampusSetting, suburban]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryCampusSetting Context triple: [University of Yaoundé II, primaryCampusSetting, suburban]
-
A.
mainCampusSetting
chosen
Indicates that an institution’s primary or central campus is used as the setting or location for the related activity or context.
-
B.
secondaryCampus
Indicates that an institution or organization has an additional, non-primary campus located at a different site.
-
C.
cityCampusServes
Indicates that a city campus provides services, resources, or support to a particular population, area, or institution.
-
D.
stateCampus
Indicates that a campus is part of, located within, or administered by a particular state.
-
E.
campusType
Indicates the classification or category of a campus based on its type (e.g., main, satellite, urban, rural).
- 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_69e25d2593c88190bcdf4a716a94ccb2 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a0aed374819097d38f51894bee44 |
completed | April 29, 2026, 6:09 a.m. |
| PD | Predicate disambiguation | batch_69f061c7aaa48190a58ce93f87155ffc |
completed | April 28, 2026, 7:29 a.m. |
Created at: April 17, 2026, 5:32 p.m.