Triple
T3841418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilmslow Rugby Club |
E93457
|
entity |
| Predicate | hasYouthSection |
P6626
|
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, hasYouthSection, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasYouthSection Context triple: [Wilmslow Rugby Club, hasYouthSection, yes]
-
A.
hasYouthProgram
chosen
Indicates that an entity offers or is associated with an organized program or set of activities specifically designed for young people.
-
B.
hasYouthTeam
Indicates that an entity has an associated youth team that serves as its junior or developmental squad.
-
C.
youthWing
Indicates that one organization serves as the youth or junior wing of another organization, typically representing younger members aligned with the parent body.
-
D.
hasStudentSection
Indicates that an entity (such as a course or class) is associated with a specific student section or subgroup of enrolled students.
-
E.
youthYears
Indicates the period of time during which an individual spent their youth, typically associated with early development or formative years, often in relation to an organization, activity, or place.
- 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_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. |
Created at: March 9, 2026, 3:18 p.m.