Triple
T32755354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Garissa |
E837605
|
entity |
| Predicate | educationInstitutionTypePresent |
P179969
|
FINISHED |
| Object | universities or university campuses |
—
|
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: universities or university campuses | Statement: [Garissa, educationInstitutionTypePresent, universities or university campuses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: educationInstitutionTypePresent Context triple: [Garissa, educationInstitutionTypePresent, universities or university campuses]
-
A.
educationType
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
-
B.
schoolTypeAttended
Indicates the specific type or category of school that an entity has attended.
-
C.
educationLocation
Indicates the place or institution where an entity received education or underwent formal learning.
-
D.
isInEducationalInstitution
Indicates that one entity is located within, enrolled in, or otherwise present at an educational institution in relation to another.
-
E.
educationStatus
Indicates the current or achieved level, stage, or condition of an entity’s formal education.
- 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_69f34937f97c8190b7f84bea045df3ae |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f72921cf2c8190909bb53f78bcc890 |
completed | May 3, 2026, 10:53 a.m. |
| PD | Predicate disambiguation | batch_69f7283d8cec8190b524c144948bc4ec |
completed | May 3, 2026, 10:49 a.m. |
| PDg | Predicate description generation | batch_69f72920c6208190aa4aba6cb6193109 |
completed | May 3, 2026, 10:53 a.m. |
Created at: May 1, 2026, 1:12 a.m.