Triple
T289851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warrington Academy |
E5964
|
entity |
| Predicate | hasEducationalPhilosophy |
P779
|
FINISHED |
| Object | rational dissent |
—
|
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: rational dissent | Statement: [Warrington Academy, hasEducationalPhilosophy, rational dissent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEducationalPhilosophy Context triple: [Warrington Academy, hasEducationalPhilosophy, rational dissent]
-
A.
hasEducationalMission
Indicates that an entity is responsible for or engaged in carrying out an educational purpose, goal, or function.
-
B.
hasEducationalRole
Indicates that an entity holds a specific function, position, or responsibility within an educational context or setting.
-
C.
hasEthicalTeaching
Indicates that one entity provides, promotes, or embodies instruction or guidance related to ethical principles, values, or moral conduct for another entity.
-
D.
hasEducationalProgram
Indicates that an entity offers, runs, or is associated with a specific educational program.
-
E.
educationalApproach
chosen
Indicates the method, strategy, or philosophy used to guide teaching and learning within an educational context.
- 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_69a25946a7ac8190a78871c210213272 |
completed | Feb. 28, 2026, 2:56 a.m. |
| NER | Named-entity recognition | batch_69a25e4df5508190ab75115ac6b3964e |
completed | Feb. 28, 2026, 3:17 a.m. |
| PD | Predicate disambiguation | batch_69a25b7d089081909810442c3d0182f6 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 3:02 a.m.