Triple
T13586495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henley Business School |
E324579
|
entity |
| Predicate | hasTripleAccreditation |
P110173
|
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: [Henley Business School, hasTripleAccreditation, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTripleAccreditation Context triple: [Henley Business School, hasTripleAccreditation, true]
-
A.
hasAccreditationType
Indicates that an entity holds or is associated with a specific category or kind of accreditation.
-
B.
accreditedTo
Indicates that official recognition, authorization, or credit for something is granted by or associated with a particular entity.
-
C.
isAccredited
Indicates that an entity has been officially recognized or certified as meeting established standards by an authorized accrediting body.
-
D.
mayAlsoBeAccreditedTo
Indicates that the credit or attribution for something can additionally be assigned to another entity beyond the primary one.
-
E.
countryOfAccreditation
Indicates the country in which an entity (such as a diplomat, embassy, or representative) is officially accredited or recognized to operate.
- 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_69d80769100c819099111274614f5ed2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb054c6008190839384ce26e8f71a |
completed | April 12, 2026, 2:46 p.m. |
| PD | Predicate disambiguation | batch_69dbae18eaf48190809e8b365856cde9 |
completed | April 12, 2026, 2:37 p.m. |
| PDg | Predicate description generation | batch_69dbaf9f3bdc8190838539aaef1f422b |
completed | April 12, 2026, 2:43 p.m. |
Created at: April 9, 2026, 9:49 p.m.