Triple
T40288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal Military College, Sandhurst |
E796
|
entity |
| Predicate | hasAdmissionType |
P58
|
FINISHED |
| Object | officer cadet selection |
—
|
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: officer cadet selection | Statement: [Royal Military College, Sandhurst, hasAdmissionType, officer cadet selection]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdmissionType Context triple: [Royal Military College, Sandhurst, hasAdmissionType, officer cadet selection]
-
A.
admissionOrder
Indicates the sequence or priority in which admissions occur or are processed relative to one another.
-
B.
admissionPolicy
chosen
Indicates the rules or criteria governing whether and how entities are allowed to be admitted or granted access.
-
C.
hasAffiliationType
Indicates that one entity is connected to another through a specified kind or category of affiliation or association.
-
D.
eligibilityCriteria
Indicates the conditions or requirements that must be satisfied for an entity to qualify for or be considered eligible for something.
-
E.
hasVisitorType
Indicates the type or category of visitor associated with an entity (e.g., guest, customer, tourist, patient).
- 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_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24b80f4a8819090d2bffe29824b90 |
completed | Feb. 28, 2026, 1:57 a.m. |
| PD | Predicate disambiguation | batch_69a24ab74c548190a54872e15c8394c3 |
completed | Feb. 28, 2026, 1:53 a.m. |
Created at: Feb. 28, 2026, 1:46 a.m.