Triple
T2143559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rectorate of the University of Havana |
E47012
|
entity |
| Predicate | hasOfficeHolderRole |
P27624
|
FINISHED |
| Object | Rector |
—
|
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: Rector | Statement: [Rectorate of the University of Havana, hasOfficeHolderRole, Rector]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOfficeHolderRole Context triple: [Rectorate of the University of Havana, hasOfficeHolderRole, Rector]
-
A.
hasOfficeHolderType
Indicates that an office or position is associated with a specific type or category of office holder (e.g., elected official, appointed official).
-
B.
officeHolderRoleFor
chosen
Indicates that a specific role or position is held by an office holder within an organization or governing body.
-
C.
memberHoldsOffice
Indicates that a member occupies or serves in a specific official position or office within an organization or governing body.
-
D.
hasPoliticalRole
Indicates that an entity holds, has held, or is assigned a specific political office, function, or position in relation to another entity or context.
-
E.
officeHolderMayBe
Indicates that a specified person is permitted or eligible to hold a particular office or position.
- 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_69a88a1933e0819094f18426ed74180f |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbeaa14bc81908486683decd7ae42 |
completed | March 7, 2026, 5:59 a.m. |
| PD | Predicate disambiguation | batch_69abbd9846e88190b6c2941dd9ce7749 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:44 p.m.