Triple

T32686650
Position Surface form Disambiguated ID Type / Status
Subject Italian Uruguayans E835743 entity
Predicate citizenshipPattern P174791 FINISHED
Object some hold dual citizenship with Italy and Uruguay 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: some hold dual citizenship with Italy and Uruguay | Statement: [Italian Uruguayans, citizenshipPattern, some hold dual citizenship with Italy and Uruguay]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: citizenshipPattern
Context triple: [Italian Uruguayans, citizenshipPattern, some hold dual citizenship with Italy and Uruguay]
  • A. definedCitizenship
    Indicates that a formal citizenship status has been legally established or specified for an entity.
  • B. citizenshipType
    Indicates the specific legal category or status of an individual's citizenship in relation to a state or country.
  • C. hasTypicalCitizenship
    Indicates that an entity is generally or commonly a citizen of a specified country or jurisdiction.
  • D. denotesCitizensOf
    Indicates that a subject entity specifies or lists the people or groups who hold citizenship of a particular place or political entity.
  • E. isCitizenOf
    Indicates that a person holds legal nationality or citizenship status in a particular country or state.
  • 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_69f3493211388190993801216afbc2a7 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6c81665688190bc0cde92cf4d619f completed May 3, 2026, 3:59 a.m.
PD Predicate disambiguation batch_69f6c3f617c08190a70ba880210f908c completed May 3, 2026, 3:41 a.m.
PDg Predicate description generation batch_69f6c77500a08190b2bdeca33bd2ac08 completed May 3, 2026, 3:56 a.m.
Created at: May 1, 2026, 1:09 a.m.