Triple
T2308818
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ogwashi-Ukwu |
E51902
|
entity |
| Predicate | hasSecondaryEducation |
P177
|
FINISHED |
| Object | secondary schools |
—
|
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: secondary schools | Statement: [Ogwashi-Ukwu, hasSecondaryEducation, secondary schools]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSecondaryEducation Context triple: [Ogwashi-Ukwu, hasSecondaryEducation, secondary schools]
-
A.
educationStatus
Indicates the current or achieved level, stage, or condition of an entity’s formal education.
-
B.
educatedAt
Indicates that an entity received education or formal training at a specified institution or place of learning.
-
C.
educationType
chosen
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
-
D.
hasEducationSetNumber
Indicates that an entity is associated with a specific numbered set or grouping of educational records or qualifications.
-
E.
requiresEducation
Indicates that performing or holding the related role, activity, or position depends on having a specified level or type of education.
- 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_69a88b0bb30c81908ded03b006d29387 |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abce1f4f0c8190a714e4dcb8449f7e |
completed | March 7, 2026, 7:05 a.m. |
| PD | Predicate disambiguation | batch_69abc58ce2a081908ce2f0cadd92e9f8 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:49 p.m.