Triple
T2583512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deputy President of the Senate of Nigeria |
E57145
|
entity |
| Predicate | requiresCitizenship |
P40423
|
FINISHED |
| Object | Nigerian citizenship |
—
|
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: Nigerian citizenship | Statement: [Deputy President of the Senate of Nigeria, requiresCitizenship, Nigerian citizenship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: requiresCitizenship Context triple: [Deputy President of the Senate of Nigeria, requiresCitizenship, Nigerian citizenship]
-
A.
definedCitizenship
Indicates that a formal citizenship status has been legally established or specified for an entity.
-
B.
hasCitizenshipRestriction
Indicates that there is a legal or policy-based limitation on who can obtain or hold citizenship in a given context.
-
C.
mayHoldCitizenshipOf
Indicates that an entity is allowed or eligible to possess citizenship status of a specified country or jurisdiction.
-
D.
acquireCitizenshipBy
Indicates the process or means by which an entity obtains or is granted citizenship through a specific method, action, or legal basis.
-
E.
countryOfCitizenship
Indicates the country in which a person or entity holds legal citizenship.
- 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_69ab4a4dca6481908c301f8e317396e7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3cb33a08190a3eae1a95e1b63bf |
completed | March 7, 2026, 7:29 a.m. |
| PD | Predicate disambiguation | batch_69abd0cfeae08190aed03866ba071c5c |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd209d934819093600889af9104c3 |
completed | March 7, 2026, 7:21 a.m. |
Created at: March 6, 2026, 9:49 p.m.