Triple
T26795261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kidderminster Carolians RFC |
E670927
|
entity |
| Predicate | hasAmateurStatus |
P7462
|
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: [Kidderminster Carolians RFC, hasAmateurStatus, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAmateurStatus Context triple: [Kidderminster Carolians RFC, hasAmateurStatus, yes]
-
A.
hasAmateurLevel
Indicates that an entity possesses an amateur level of skill, experience, or proficiency in a given activity or domain.
-
B.
isAmateur
chosen
Indicates that an entity engages in an activity or field on a non-professional, typically unpaid or hobbyist basis.
-
C.
hasAmateurSection
Indicates that something includes or provides a dedicated section or part specifically for amateurs.
-
D.
wasAmateurOrSemiPro
Indicates that the subject participated in an activity at an amateur or semi-professional level, rather than as a full professional.
-
E.
isAmateurOrProfessional
Indicates that an entity participates in an activity either at an amateur level or a professional level.
- 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_69eeb31fbd888190a82dac5822e453bc |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f619bf8738819094583140287f42f0 |
completed | May 2, 2026, 3:35 p.m. |
| PD | Predicate disambiguation | batch_69f611ad2eb48190ac1ed0090f13f7a9 |
completed | May 2, 2026, 3:01 p.m. |
Created at: April 27, 2026, 4:19 a.m.