Triple
T7800491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St Benedict's School, Ealing |
E180416
|
entity |
| Predicate | hasJuniorSection |
P79082
|
FINISHED |
| Object | junior school |
—
|
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: junior school | Statement: [St Benedict's School, Ealing, hasJuniorSection, junior school]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasJuniorSection Context triple: [St Benedict's School, Ealing, hasJuniorSection, junior school]
-
A.
hasJuniorStatus
Indicates that one entity holds a lower, subordinate, or less senior status relative to another entity within a defined hierarchy or context.
-
B.
hasSeniorSection
Indicates that an entity includes or is associated with a designated section or area specifically intended for seniors.
-
C.
hasJuniorSystem
Indicates that an entity has another entity associated with it in a subordinate or lower-level system role or configuration.
-
D.
hasTeenSection
Indicates that an entity includes or provides a designated section or area specifically intended for teenagers.
-
E.
hasChildrenSection
Indicates that an entity includes or is associated with a dedicated section that contains information about its children.
- 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_69ca827e50cc8190a92a733577184938 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf78a6d88819093f83528fe88b182 |
completed | March 30, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69cae9111b2481909684a2d4aa4831c2 |
completed | March 30, 2026, 9:20 p.m. |
| PDg | Predicate description generation | batch_69caf7855a3c81908b9318f7186fc0c0 |
completed | March 30, 2026, 10:21 p.m. |
Created at: March 30, 2026, 4:33 p.m.