Triple

T562046
Position Surface form Disambiguated ID Type / Status
Subject Djibouti E13472 entity
Predicate nationalityLaw P4308 FINISHED
Object citizenship by descent and naturalization 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: citizenship by descent and naturalization | Statement: [Djibouti, nationalityLaw, citizenship by descent and naturalization]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: nationalityLaw
Context triple: [Djibouti, nationalityLaw, citizenship by descent and naturalization]
  • A. namedAfterCountryOfCitizenship
    Indicates that something is named after the country where a person holds citizenship.
  • B. laterCitizenship
    Indicates that an entity acquired citizenship in a country or polity at a later point in time, after some earlier status or affiliation.
  • C. countryOfCitizenship
    Indicates the country in which a person or entity holds legal citizenship.
  • D. acquireCitizenshipBy chosen
    Indicates the process or means by which an entity obtains or is granted citizenship through a specific method, action, or legal basis.
  • E. citizenshipLinkedTo
    Indicates that there is an established connection between an entity and a specific citizenship status, such as holding, sharing, or being associated with that citizenship.
  • 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_69a4933edcf08190b35ecfd6014caee6 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49a700e608190b235246df057bd9b completed March 1, 2026, 7:58 p.m.
PD Predicate disambiguation batch_69a494befb8481908bb4e2e9f31e343b completed March 1, 2026, 7:34 p.m.
Created at: March 1, 2026, 7:32 p.m.