Triple
T2295605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal Holloway, University of London |
E51604
|
entity |
| Predicate | hasRectorOrEquivalent |
P7006
|
FINISHED |
| Object | Principal |
—
|
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: Principal | Statement: [Royal Holloway, University of London, hasRectorOrEquivalent, Principal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRectorOrEquivalent Context triple: [Royal Holloway, University of London, hasRectorOrEquivalent, Principal]
-
A.
hasEquivalent
Indicates that two entities are considered equal in value, meaning, or function within a given context.
-
B.
hasEquivalentRole
chosen
Indicates that two entities hold roles that are functionally the same or interchangeable in a given context.
-
C.
hasVersionIn
Indicates that one entity exists as a specific version or variant within the context, format, or system represented by another entity.
-
D.
hasMCR
Indicates a relationship where an entity is associated with, or possesses, a specific MCR (e.g., a defined minimum capital requirement or similarly named regulatory/technical measure).
-
E.
hasCP
Indicates that an entity possesses, is associated with, or is characterized by a specific CP (such as a control point, contact person, or configuration parameter), depending on the domain context.
- 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_69a88b0a9f248190bcff941463d8f65a |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abcd0e42248190ada33b84d75caa64 |
completed | March 7, 2026, 7 a.m. |
| PD | Predicate disambiguation | batch_69abc589295c819092989820c2b4e9d8 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:49 p.m.