Triple
T18812497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Albany, Auckland |
E460049
|
entity |
| Predicate | educationLevelNearby |
P21535
|
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: [Albany, Auckland, educationLevelNearby, secondary schools]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: educationLevelNearby Context triple: [Albany, Auckland, educationLevelNearby, secondary schools]
-
A.
educationType
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
-
B.
educationLevelCharacteristic
chosen
Indicates that one entity specifies, describes, or constrains the education level associated with another entity.
-
C.
educationStatus
Indicates the current or achieved level, stage, or condition of an entity’s formal education.
-
D.
educationLocation
Indicates the place or institution where an entity received education or underwent formal learning.
-
E.
educationIndicator
Indicates that there is a measure or metric reflecting some aspect of educational status, performance, or outcomes associated with the 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_69d8d398c7d4819091cb2f7e48948aeb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5a3dcc7d88190801d9c9202e0e411 |
completed | April 20, 2026, 3:56 a.m. |
| PD | Predicate disambiguation | batch_69e48d1b10ec8190985c6fb5766ff981 |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:53 a.m.