Triple
T33292793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cypriot passports |
E852358
|
entity |
| Predicate | citizenshipConferred |
P81741
|
FINISHED |
| Object | Cypriot 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: Cypriot citizenship | Statement: [Cypriot passports, citizenshipConferred, Cypriot citizenship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: citizenshipConferred Context triple: [Cypriot passports, citizenshipConferred, Cypriot citizenship]
-
A.
grantedCitizenshipBy
chosen
Indicates that one entity has officially conferred citizenship status upon another entity.
-
B.
citizenshipGrantedYear
Indicates the specific year in which an entity was officially granted citizenship.
-
C.
definedCitizenship
Indicates that a formal citizenship status has been legally established or specified for an entity.
-
D.
citizenshipBasedOn
Indicates that an entity’s citizenship is determined or derived from another specified factor, condition, or relationship.
-
E.
citizenshipContext
Indicates the legal or social circumstances under which an entity holds or is granted citizenship in a particular state or jurisdiction.
- 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_69f349660ff48190a4568803d0b89941 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6e3156ea48190b604e414665ef351 |
completed | May 3, 2026, 5:54 a.m. |
| PD | Predicate disambiguation | batch_69f6de0b9ba48190887c9eb5d06a2e94 |
completed | May 3, 2026, 5:32 a.m. |
Created at: May 1, 2026, 1:33 a.m.