Triple
T16970177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leehurst Swan School |
E411648
|
entity |
| Predicate | hasPrimarySection |
P125437
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Leehurst Swan School, hasPrimarySection, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimarySection Context triple: [Leehurst Swan School, hasPrimarySection, true]
-
A.
hasPrimary
Indicates that one entity is designated as the main or most important instance (the primary) in relation to another entity.
-
B.
hasMainSectionStyle
Indicates that an entity is associated with a primary or dominant style used for its main section or main content area.
-
C.
hasSectionOn
Indicates that one entity (typically a document or resource) contains a dedicated section or part that specifically addresses or discusses another entity or topic.
-
D.
hasCentralSection
Indicates that an entity possesses a distinct middle or central part within its overall structure or composition.
-
E.
hasVerticalSection
Indicates that one entity possesses or includes a distinct vertical section or segment as part of its structure or representation.
- 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_69d886ca8f348190812768ea8d5055ce |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d0ac23a48190992fa125fceb1eb2 |
completed | April 18, 2026, 6:42 p.m. |
| PD | Predicate disambiguation | batch_69e35d4dff4881909b384e30f2d36bff |
completed | April 18, 2026, 10:30 a.m. |
| PDg | Predicate description generation | batch_69e3753f93c88190808fec5692f66699 |
completed | April 18, 2026, 12:12 p.m. |
Created at: April 10, 2026, 5:31 a.m.