Triple

T3570314
Position Surface form Disambiguated ID Type / Status
Subject Vatican citizen E75553 entity
Predicate dualCitizenship P13473 FINISHED
Object often also citizen of another state 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: often also citizen of another state | Statement: [Vatican citizen, dualCitizenship, often also citizen of another state]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: dualCitizenship
Context triple: [Vatican citizen, dualCitizenship, often also citizen of another state]
  • A. hasDualCitizenship chosen
    Indicates that a person is legally recognized as a citizen of two different countries at the same time.
  • B. dualCitizenshipStatus
    Indicates that an entity holds legal citizenship in two different countries simultaneously.
  • C. mayHoldDualCitizenshipWith
    Indicates that an entity is allowed to simultaneously hold citizenship in the specified other country or jurisdiction.
  • D. mayHoldCitizenshipOf
    Indicates that an entity is allowed or eligible to possess citizenship status of a specified country or jurisdiction.
  • E. definedCitizenship
    Indicates that a formal citizenship status has been legally established or specified for an entity.
  • 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_69ad85d512708190829c8b2d3a2ccfb8 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc0c1ecb081909051bcc1f38eea31 completed March 8, 2026, 6:32 p.m.
PD Predicate disambiguation batch_69adb8364d848190a96a9bc7a6126af2 completed March 8, 2026, 5:56 p.m.
Created at: March 8, 2026, 3:21 p.m.