Triple
T12361067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ethel Walker School |
E294736
|
entity |
| Predicate | hasStrongFocus |
P10167
|
FINISHED |
| Object | rigorous academics |
—
|
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: rigorous academics | Statement: [Ethel Walker School, hasStrongFocus, rigorous academics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStrongFocus Context triple: [Ethel Walker School, hasStrongFocus, rigorous academics]
-
A.
hasPrimaryFocus
chosen
Indicates that something is the main subject, concern, or area of attention for an entity or activity.
-
B.
hasVisualFocus
Indicates that one entity is currently directing its visual attention or gaze toward another entity.
-
C.
hasRDFocus
Indicates that something has a specific region of interest or focal area within an image, scene, or dataset that is being emphasized or analyzed.
-
D.
hasAccessibilityFocus
Indicates that a user interface element is currently the primary target of accessibility tools, such as screen readers or keyboard navigation, receiving focused attention for interaction.
-
E.
hasCharacterFocus
Indicates that a work, scene, or segment centers primarily on a particular character’s experiences, perspective, or development.
- 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_69d6ab6d8a4081908636601e69ddf262 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d942a2d6e08190a13c7ff89af09354 |
completed | April 10, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69d93ecf6b548190a394b6b56a0c1c68 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:54 p.m.