Triple
T3841419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilmslow Rugby Club |
E93457
|
entity |
| Predicate | hasSeniorSection |
P52338
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Wilmslow Rugby Club, hasSeniorSection, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeniorSection Context triple: [Wilmslow Rugby Club, hasSeniorSection, yes]
-
A.
hasStudentSection
Indicates that an entity (such as a course or class) is associated with a specific student section or subgroup of enrolled students.
-
B.
hasSect
Indicates that an entity includes, contains, or is associated with a particular sect or subgroup within a larger religious, ideological, or organizational context.
-
C.
hasCentralSection
Indicates that an entity possesses a distinct middle or central part within its overall structure or composition.
-
D.
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.
-
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_69aed96ce578819084ab16e3439976c9 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aeebb235088190b115623e54ea2ab1 |
completed | March 9, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69aee74dcecc819098285483ec721b40 |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aeeb828fb08190901d51edbe8bd304 |
completed | March 9, 2026, 3:47 p.m. |
Created at: March 9, 2026, 3:18 p.m.