Triple
T27129576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moore Park campus |
E681526
|
entity |
| Predicate | schoolSelectionType |
P165380
|
FINISHED |
| Object | selective |
—
|
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: selective | Statement: [Moore Park campus, schoolSelectionType, selective]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: schoolSelectionType Context triple: [Moore Park campus, schoolSelectionType, selective]
-
A.
schoolSystemType
Indicates the classification or organizational model of a school system (e.g., public, private, charter, or other structural type).
-
B.
schoolBoardSelectionMethod
Indicates how members of a school board are chosen or appointed.
-
C.
schoolTypeOffered
Indicates the specific type or category of school that is provided or made available by an educational institution or organization.
-
D.
schoolTypeAttended
Indicates the specific type or category of school that an entity has attended.
-
E.
schoolSector
Indicates the educational sector or category (such as public, private, or charter) to which a school belongs.
- 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_69eefacbcc2081909ebf00daa23f1981 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f659355a208190be2609ffc7a9c427 |
completed | May 2, 2026, 8:06 p.m. |
| PD | Predicate disambiguation | batch_69f6575d89788190aca478e4aea05a65 |
completed | May 2, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69f65875030881909007c502b7dcc998 |
completed | May 2, 2026, 8:03 p.m. |
Created at: April 27, 2026, 9:03 a.m.